{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Requirement already satisfied: importlib-metadata>=4.4 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (5.1.0)\n",
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      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.12.7)\n",
      "Requirement already satisfied: MarkupSafe>=2.1.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from werkzeug>=1.0.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.1.1)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.11.0)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.2.2)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflow"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.5.2)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: numpy>=1.20.3 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (1.23.5)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from pandas) (2022.6)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: neural_structured_learning in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.4.0)\n",
      "Requirement already satisfied: absl-py in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.3.0)\n",
      "Requirement already satisfied: six in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.16.0)\n",
      "Requirement already satisfied: attrs in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (22.1.0)\n",
      "Requirement already satisfied: scipy in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from neural_structured_learning) (1.9.3)\n",
      "Requirement already satisfied: numpy<1.26.0,>=1.18.5 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scipy->neural_structured_learning) (1.23.5)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install neural_structured_learning"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scikit_learn in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (1.2.0)\n",
      "Requirement already satisfied: scipy>=1.3.2 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.9.3)\n",
      "Requirement already satisfied: joblib>=1.1.1 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.2.0)\n",
      "Requirement already satisfied: numpy>=1.17.3 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (1.23.5)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\fer_u\\pycharmprojects\\cyberattacksattention\\venv\\lib\\site-packages (from scikit_learn) (3.1.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.3.1; however, version 22.3.1 is available.\n",
      "You should consider upgrading via the 'C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\Scripts\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install scikit_learn"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "executionInfo": {
     "elapsed": 4460,
     "status": "ok",
     "timestamp": 1670604423667,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "bTL3Ufo0t487",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import pandas as pd\n",
    "import neural_structured_learning as nsl\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "executionInfo": {
     "elapsed": 1214,
     "status": "ok",
     "timestamp": 1670604426852,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "xdB9GixktNz0",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('ICSX_URL_2017/Defacement.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 300
    },
    "executionInfo": {
     "elapsed": 14,
     "status": "ok",
     "timestamp": 1670604426856,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "856UWFEmyUms",
    "outputId": "a5a2bcaf-4a37-454e-eb77-2ffe6b9b956f",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "   Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0            0                   4                 5                5.5   \n1            0                   4                 5                5.5   \n2            0                   4                 5                5.5   \n3            0                   4                12                5.5   \n4            0                   4                 6                5.5   \n\n   longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                  14         4.400000    4               8            3   \n1                  14         6.000000    4              12            4   \n2                  14         5.800000    4              12            5   \n3                  14         5.500000    4              32           16   \n4                  14         7.333334    4              18           11   \n\n   ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0        0  ...                     1                      0   \n1        0  ...                     0                      0   \n2        0  ...                     0                      0   \n3        0  ...                     0                      0   \n4        0  ...                     0                      0   \n\n   SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  Entropy_DirectoryName  \\\n0                     -1     0.726298        0.784493               0.894886   \n1                     -1     0.688635        0.784493               0.814725   \n2                     -1     0.695049        0.784493               0.814725   \n3                     -1     0.640130        0.784493               0.814725   \n4                     -1     0.681307        0.784493               0.814725   \n\n   Entropy_Filename  Entropy_Extension  Entropy_Afterpath  URL_Type_obf_Type  \n0          0.850608                NaN               -1.0         Defacement  \n1          0.859793                0.0               -1.0         Defacement  \n2          0.801880                0.0               -1.0         Defacement  \n3          0.663210                0.0               -1.0         Defacement  \n4          0.804526                0.0               -1.0         Defacement  \n\n[5 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5.5</td>\n      <td>14</td>\n      <td>4.400000</td>\n      <td>4</td>\n      <td>8</td>\n      <td>3</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.726298</td>\n      <td>0.784493</td>\n      <td>0.894886</td>\n      <td>0.850608</td>\n      <td>NaN</td>\n      <td>-1.0</td>\n      <td>Defacement</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5.5</td>\n      <td>14</td>\n      <td>6.000000</td>\n      <td>4</td>\n      <td>12</td>\n      <td>4</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.688635</td>\n      <td>0.784493</td>\n      <td>0.814725</td>\n      <td>0.859793</td>\n      <td>0.0</td>\n      <td>-1.0</td>\n      <td>Defacement</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5.5</td>\n      <td>14</td>\n      <td>5.800000</td>\n      <td>4</td>\n      <td>12</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.695049</td>\n      <td>0.784493</td>\n      <td>0.814725</td>\n      <td>0.801880</td>\n      <td>0.0</td>\n      <td>-1.0</td>\n      <td>Defacement</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n      <td>4</td>\n      <td>12</td>\n      <td>5.5</td>\n      <td>14</td>\n      <td>5.500000</td>\n      <td>4</td>\n      <td>32</td>\n      <td>16</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.640130</td>\n      <td>0.784493</td>\n      <td>0.814725</td>\n      <td>0.663210</td>\n      <td>0.0</td>\n      <td>-1.0</td>\n      <td>Defacement</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n      <td>4</td>\n      <td>6</td>\n      <td>5.5</td>\n      <td>14</td>\n      <td>7.333334</td>\n      <td>4</td>\n      <td>18</td>\n      <td>11</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.681307</td>\n      <td>0.784493</td>\n      <td>0.814725</td>\n      <td>0.804526</td>\n      <td>0.0</td>\n      <td>-1.0</td>\n      <td>Defacement</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1670604426856,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "mkez4dRDyZ4L",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "features = len(df.columns) - 1\n",
    "label_encoder = LabelEncoder()\n",
    "df = df.dropna()\n",
    "df = df.reset_index(drop=True)\n",
    "df['URL_Type_obf_Type'] = label_encoder.fit_transform(df['URL_Type_obf_Type'])\n",
    "classes = df['URL_Type_obf_Type'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 10,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "6wz-53mHnm7p",
    "outputId": "fe64ae3c-8710-4fbe-fc93-ff39924faffd",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "      Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0               0                   4                 4           6.250000   \n1              22                   4                10           6.250000   \n2              23                   4                10           6.250000   \n3              22                   4                10           6.250000   \n4              23                   4                10           6.250000   \n...           ...                 ...               ...                ...   \n5181            0                   2                12           4.000000   \n5182            0                   2                13           5.000000   \n5183            0                   2                10           4.000000   \n5184            0                   3                17           4.333334   \n5185            0                   2                12           4.500000   \n\n      longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                     17         3.750000    4               4            2   \n1                     17         3.500000    4              19           10   \n2                     17         3.500000    4              19           10   \n3                     17         3.500000    4              19           10   \n4                     17         3.500000    4              19           10   \n...                  ...              ...  ...             ...          ...   \n5181                   6         4.083334    2              10            8   \n5182                   7         4.692308    2              19           12   \n5183                   5         3.500000    2              10            4   \n5184                   8         3.705882    3              21           14   \n5185                   7         4.916666    2              15           10   \n\n      ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0           0  ...                     1                      0   \n1           0  ...                     9                      8   \n2           0  ...                     9                      8   \n3           0  ...                     9                      8   \n4           0  ...                     9                      8   \n...       ...  ...                   ...                    ...   \n5181        1  ...                     1                      0   \n5182        0  ...                    -1                     -1   \n5183        0  ...                     1                      0   \n5184        0  ...                     1                      0   \n5185        1  ...                     1                      0   \n\n      SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  \\\n0                        -1     0.726945        0.768811   \n1                         7     0.686486        0.768811   \n2                         7     0.687286        0.768811   \n3                         7     0.683476        0.768811   \n4                         7     0.687286        0.768811   \n...                     ...          ...             ...   \n5181                     -1     0.736381        0.929897   \n5182                     -1     0.705179        0.875048   \n5183                     -1     0.768122        0.929897   \n5184                     -1     0.656904        0.816480   \n5185                     -1     0.723462        0.698970   \n\n      Entropy_DirectoryName  Entropy_Filename  Entropy_Extension  \\\n0                  0.916667          1.000000           1.000000   \n1                  0.916667          0.748105           0.757206   \n2                  0.916667          0.747622           0.756298   \n3                  0.916667          0.742090           0.750292   \n4                  0.916667          0.747622           0.756298   \n...                     ...               ...                ...   \n5181               0.871049          0.733788           1.000000   \n5182              -1.000000         -1.000000          -1.000000   \n5183               0.820507          0.849605           1.000000   \n5184               0.894886          0.665891           1.000000   \n5185               0.916667          0.767379           1.000000   \n\n      Entropy_Afterpath  URL_Type_obf_Type  \n0             -1.000000                  0  \n1              0.749167                  0  \n2              0.748268                  0  \n3              0.741506                  0  \n4              0.748268                  0  \n...                 ...                ...  \n5181          -1.000000                  1  \n5182          -1.000000                  1  \n5183          -1.000000                  1  \n5184          -1.000000                  1  \n5185          -1.000000                  1  \n\n[5186 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>4</td>\n      <td>4</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.750000</td>\n      <td>4</td>\n      <td>4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.726945</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>22</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.686486</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.748105</td>\n      <td>0.757206</td>\n      <td>0.749167</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>23</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.687286</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.747622</td>\n      <td>0.756298</td>\n      <td>0.748268</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>22</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.683476</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.742090</td>\n      <td>0.750292</td>\n      <td>0.741506</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>23</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.687286</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.747622</td>\n      <td>0.756298</td>\n      <td>0.748268</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>5181</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>4.000000</td>\n      <td>6</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>10</td>\n      <td>8</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.736381</td>\n      <td>0.929897</td>\n      <td>0.871049</td>\n      <td>0.733788</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5182</th>\n      <td>0</td>\n      <td>2</td>\n      <td>13</td>\n      <td>5.000000</td>\n      <td>7</td>\n      <td>4.692308</td>\n      <td>2</td>\n      <td>19</td>\n      <td>12</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.705179</td>\n      <td>0.875048</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5183</th>\n      <td>0</td>\n      <td>2</td>\n      <td>10</td>\n      <td>4.000000</td>\n      <td>5</td>\n      <td>3.500000</td>\n      <td>2</td>\n      <td>10</td>\n      <td>4</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.768122</td>\n      <td>0.929897</td>\n      <td>0.820507</td>\n      <td>0.849605</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5184</th>\n      <td>0</td>\n      <td>3</td>\n      <td>17</td>\n      <td>4.333334</td>\n      <td>8</td>\n      <td>3.705882</td>\n      <td>3</td>\n      <td>21</td>\n      <td>14</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.656904</td>\n      <td>0.816480</td>\n      <td>0.894886</td>\n      <td>0.665891</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5185</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>4.500000</td>\n      <td>7</td>\n      <td>4.916666</td>\n      <td>2</td>\n      <td>15</td>\n      <td>10</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.723462</td>\n      <td>0.698970</td>\n      <td>0.916667</td>\n      <td>0.767379</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>5186 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 331
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "pDdBjmOgVZdA",
    "outputId": "649a90de-aad7-4207-a533-07f3a793c1d5",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                   Querylength  domain_token_count  path_token_count  \\\nURL_Type_obf_Type                                                      \n0                         2477                2477              2477   \n1                         2709                2709              2709   \n\n                   avgdomaintokenlen  longdomaintokenlen  avgpathtokenlen  \\\nURL_Type_obf_Type                                                           \n0                               2477                2477             2477   \n1                               2709                2709             2709   \n\n                    tld  charcompvowels  charcompace  ldl_url  ...  \\\nURL_Type_obf_Type                                              ...   \n0                  2477            2477         2477     2477  ...   \n1                  2709            2709         2709     2709  ...   \n\n                   SymbolCount_Directoryname  SymbolCount_FileName  \\\nURL_Type_obf_Type                                                    \n0                                       2477                  2477   \n1                                       2709                  2709   \n\n                   SymbolCount_Extension  SymbolCount_Afterpath  Entropy_URL  \\\nURL_Type_obf_Type                                                              \n0                                   2477                   2477         2477   \n1                                   2709                   2709         2709   \n\n                   Entropy_Domain  Entropy_DirectoryName  Entropy_Filename  \\\nURL_Type_obf_Type                                                            \n0                            2477                   2477              2477   \n1                            2709                   2709              2709   \n\n                   Entropy_Extension  Entropy_Afterpath  \nURL_Type_obf_Type                                        \n0                               2477               2477  \n1                               2709               2709  \n\n[2 rows x 79 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_Directoryname</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n    </tr>\n    <tr>\n      <th>URL_Type_obf_Type</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>...</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n      <td>2477</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>...</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n      <td>2709</td>\n    </tr>\n  </tbody>\n</table>\n<p>2 rows × 79 columns</p>\n</div>"
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('URL_Type_obf_Type').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "executionInfo": {
     "elapsed": 8,
     "status": "ok",
     "timestamp": 1670604426857,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "5MKUhTHEVvn8",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df_0 = df.loc[df['URL_Type_obf_Type'] == 0]\n",
    "df_1 = df.loc[df['URL_Type_obf_Type'] == 1]\n",
    "df_2 = df.loc[df['URL_Type_obf_Type'] == 2]\n",
    "df_3 = df.loc[df['URL_Type_obf_Type'] == 3]\n",
    "df_4 = df.loc[df['URL_Type_obf_Type'] == 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "executionInfo": {
     "elapsed": 413,
     "status": "ok",
     "timestamp": 1670604427263,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "VBg_I0QKXFk0",
    "outputId": "761a2fc5-02e5-46f0-eb8a-f7fd4f9bc9a0",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "      Querylength  domain_token_count  path_token_count  avgdomaintokenlen  \\\n0               0                   4                 4           6.250000   \n1              22                   4                10           6.250000   \n2              23                   4                10           6.250000   \n3              22                   4                10           6.250000   \n4              23                   4                10           6.250000   \n...           ...                 ...               ...                ...   \n5181            0                   2                12           4.000000   \n5182            0                   2                13           5.000000   \n5183            0                   2                10           4.000000   \n5184            0                   3                17           4.333334   \n5185            0                   2                12           4.500000   \n\n      longdomaintokenlen  avgpathtokenlen  tld  charcompvowels  charcompace  \\\n0                     17         3.750000    4               4            2   \n1                     17         3.500000    4              19           10   \n2                     17         3.500000    4              19           10   \n3                     17         3.500000    4              19           10   \n4                     17         3.500000    4              19           10   \n...                  ...              ...  ...             ...          ...   \n5181                   6         4.083334    2              10            8   \n5182                   7         4.692308    2              19           12   \n5183                   5         3.500000    2              10            4   \n5184                   8         3.705882    3              21           14   \n5185                   7         4.916666    2              15           10   \n\n      ldl_url  ...  SymbolCount_FileName  SymbolCount_Extension  \\\n0           0  ...                     1                      0   \n1           0  ...                     9                      8   \n2           0  ...                     9                      8   \n3           0  ...                     9                      8   \n4           0  ...                     9                      8   \n...       ...  ...                   ...                    ...   \n5181        1  ...                     1                      0   \n5182        0  ...                    -1                     -1   \n5183        0  ...                     1                      0   \n5184        0  ...                     1                      0   \n5185        1  ...                     1                      0   \n\n      SymbolCount_Afterpath  Entropy_URL  Entropy_Domain  \\\n0                        -1     0.726945        0.768811   \n1                         7     0.686486        0.768811   \n2                         7     0.687286        0.768811   \n3                         7     0.683476        0.768811   \n4                         7     0.687286        0.768811   \n...                     ...          ...             ...   \n5181                     -1     0.736381        0.929897   \n5182                     -1     0.705179        0.875048   \n5183                     -1     0.768122        0.929897   \n5184                     -1     0.656904        0.816480   \n5185                     -1     0.723462        0.698970   \n\n      Entropy_DirectoryName  Entropy_Filename  Entropy_Extension  \\\n0                  0.916667          1.000000           1.000000   \n1                  0.916667          0.748105           0.757206   \n2                  0.916667          0.747622           0.756298   \n3                  0.916667          0.742090           0.750292   \n4                  0.916667          0.747622           0.756298   \n...                     ...               ...                ...   \n5181               0.871049          0.733788           1.000000   \n5182              -1.000000         -1.000000          -1.000000   \n5183               0.820507          0.849605           1.000000   \n5184               0.894886          0.665891           1.000000   \n5185               0.916667          0.767379           1.000000   \n\n      Entropy_Afterpath  URL_Type_obf_Type  \n0             -1.000000                  0  \n1              0.749167                  0  \n2              0.748268                  0  \n3              0.741506                  0  \n4              0.748268                  0  \n...                 ...                ...  \n5181          -1.000000                  1  \n5182          -1.000000                  1  \n5183          -1.000000                  1  \n5184          -1.000000                  1  \n5185          -1.000000                  1  \n\n[5186 rows x 80 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Querylength</th>\n      <th>domain_token_count</th>\n      <th>path_token_count</th>\n      <th>avgdomaintokenlen</th>\n      <th>longdomaintokenlen</th>\n      <th>avgpathtokenlen</th>\n      <th>tld</th>\n      <th>charcompvowels</th>\n      <th>charcompace</th>\n      <th>ldl_url</th>\n      <th>...</th>\n      <th>SymbolCount_FileName</th>\n      <th>SymbolCount_Extension</th>\n      <th>SymbolCount_Afterpath</th>\n      <th>Entropy_URL</th>\n      <th>Entropy_Domain</th>\n      <th>Entropy_DirectoryName</th>\n      <th>Entropy_Filename</th>\n      <th>Entropy_Extension</th>\n      <th>Entropy_Afterpath</th>\n      <th>URL_Type_obf_Type</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>4</td>\n      <td>4</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.750000</td>\n      <td>4</td>\n      <td>4</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.726945</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>22</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.686486</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.748105</td>\n      <td>0.757206</td>\n      <td>0.749167</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>23</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.687286</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.747622</td>\n      <td>0.756298</td>\n      <td>0.748268</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>22</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.683476</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.742090</td>\n      <td>0.750292</td>\n      <td>0.741506</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>23</td>\n      <td>4</td>\n      <td>10</td>\n      <td>6.250000</td>\n      <td>17</td>\n      <td>3.500000</td>\n      <td>4</td>\n      <td>19</td>\n      <td>10</td>\n      <td>0</td>\n      <td>...</td>\n      <td>9</td>\n      <td>8</td>\n      <td>7</td>\n      <td>0.687286</td>\n      <td>0.768811</td>\n      <td>0.916667</td>\n      <td>0.747622</td>\n      <td>0.756298</td>\n      <td>0.748268</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>5181</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>4.000000</td>\n      <td>6</td>\n      <td>4.083334</td>\n      <td>2</td>\n      <td>10</td>\n      <td>8</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.736381</td>\n      <td>0.929897</td>\n      <td>0.871049</td>\n      <td>0.733788</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5182</th>\n      <td>0</td>\n      <td>2</td>\n      <td>13</td>\n      <td>5.000000</td>\n      <td>7</td>\n      <td>4.692308</td>\n      <td>2</td>\n      <td>19</td>\n      <td>12</td>\n      <td>0</td>\n      <td>...</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>-1</td>\n      <td>0.705179</td>\n      <td>0.875048</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5183</th>\n      <td>0</td>\n      <td>2</td>\n      <td>10</td>\n      <td>4.000000</td>\n      <td>5</td>\n      <td>3.500000</td>\n      <td>2</td>\n      <td>10</td>\n      <td>4</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.768122</td>\n      <td>0.929897</td>\n      <td>0.820507</td>\n      <td>0.849605</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5184</th>\n      <td>0</td>\n      <td>3</td>\n      <td>17</td>\n      <td>4.333334</td>\n      <td>8</td>\n      <td>3.705882</td>\n      <td>3</td>\n      <td>21</td>\n      <td>14</td>\n      <td>0</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.656904</td>\n      <td>0.816480</td>\n      <td>0.894886</td>\n      <td>0.665891</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>5185</th>\n      <td>0</td>\n      <td>2</td>\n      <td>12</td>\n      <td>4.500000</td>\n      <td>7</td>\n      <td>4.916666</td>\n      <td>2</td>\n      <td>15</td>\n      <td>10</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>0</td>\n      <td>-1</td>\n      <td>0.723462</td>\n      <td>0.698970</td>\n      <td>0.916667</td>\n      <td>0.767379</td>\n      <td>1.000000</td>\n      <td>-1.000000</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>5186 rows × 80 columns</p>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df_0, df_1, df_2, df_3, df_4])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "9s_HaYjkzuKk",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "y = df.pop('URL_Type_obf_Type')\n",
    "X = df\n",
    "\n",
    "normalizer_scaler = preprocessing.Normalizer()\n",
    "x_scaled = normalizer_scaler.fit_transform(X)\n",
    "X = pd.DataFrame(x_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "l-9LdOome2ck",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1670604427264,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "FC6lXk4Az3yB",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_train = tf.convert_to_tensor(X_train)\n",
    "y_train = tf.convert_to_tensor(y_train)\n",
    "\n",
    "X_test = tf.convert_to_tensor(X_test)\n",
    "y_test = tf.convert_to_tensor(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "executionInfo": {
     "elapsed": 333,
     "status": "ok",
     "timestamp": 1670604427594,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "SP8ckOayytne",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "input = tf.keras.layers.Input((features,), name='feature')\n",
    "\n",
    "n1 = tf.keras.layers.Dense(32)(input)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(64)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(128)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(256)(n1)\n",
    "\n",
    "n1 = tf.keras.layers.MultiHeadAttention(num_heads=int(256/8), key_dim=256, value_dim=256, attention_axes=1)(n1, n1, n1)\n",
    "\n",
    "n1 = tf.keras.layers.Dense(256)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(128)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(64)(n1)\n",
    "n1 = tf.keras.layers.Dropout(0.25)(n1)\n",
    "n1 = tf.keras.layers.Dense(32)(n1)\n",
    "\n",
    "output = tf.keras.layers.Dense(classes, activation='softmax')(n1)\n",
    "\n",
    "model = tf.keras.Model(inputs=input, outputs=output)\n",
    "\n",
    "adv_config = nsl.configs.make_adv_reg_config(multiplier=0.2, adv_step_size=0.05)\n",
    "adv_model = nsl.keras.AdversarialRegularization(model, adv_config=adv_config)\n",
    "\n",
    "# Compile, train, and evaluate.\n",
    "adv_model.compile(optimizer='adam',\n",
    "                  loss='sparse_categorical_crossentropy',\n",
    "                  metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 269,
     "status": "ok",
     "timestamp": 1670604427855,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "-EUxz4vRy7YP",
    "outputId": "1c8c1a81-6e6b-4129-f8a2-9d22f904cb87",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " feature (InputLayer)           [(None, 79)]         0           []                               \n",
      "                                                                                                  \n",
      " dense (Dense)                  (None, 32)           2560        ['feature[0][0]']                \n",
      "                                                                                                  \n",
      " dropout (Dropout)              (None, 32)           0           ['dense[0][0]']                  \n",
      "                                                                                                  \n",
      " dense_1 (Dense)                (None, 64)           2112        ['dropout[0][0]']                \n",
      "                                                                                                  \n",
      " dropout_1 (Dropout)            (None, 64)           0           ['dense_1[0][0]']                \n",
      "                                                                                                  \n",
      " dense_2 (Dense)                (None, 128)          8320        ['dropout_1[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_2 (Dropout)            (None, 128)          0           ['dense_2[0][0]']                \n",
      "                                                                                                  \n",
      " dense_3 (Dense)                (None, 256)          33024       ['dropout_2[0][0]']              \n",
      "                                                                                                  \n",
      " multi_head_attention (MultiHea  (None, 256)         8413440     ['dense_3[0][0]',                \n",
      " dAttention)                                                      'dense_3[0][0]',                \n",
      "                                                                  'dense_3[0][0]']                \n",
      "                                                                                                  \n",
      " dense_4 (Dense)                (None, 256)          65792       ['multi_head_attention[0][0]']   \n",
      "                                                                                                  \n",
      " dropout_3 (Dropout)            (None, 256)          0           ['dense_4[0][0]']                \n",
      "                                                                                                  \n",
      " dense_5 (Dense)                (None, 128)          32896       ['dropout_3[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_4 (Dropout)            (None, 128)          0           ['dense_5[0][0]']                \n",
      "                                                                                                  \n",
      " dense_6 (Dense)                (None, 64)           8256        ['dropout_4[0][0]']              \n",
      "                                                                                                  \n",
      " dropout_5 (Dropout)            (None, 64)           0           ['dense_6[0][0]']                \n",
      "                                                                                                  \n",
      " dense_7 (Dense)                (None, 32)           2080        ['dropout_5[0][0]']              \n",
      "                                                                                                  \n",
      " dense_8 (Dense)                (None, 2)            66          ['dense_7[0][0]']                \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 8,568,546\n",
      "Trainable params: 8,568,546\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 48
    },
    "executionInfo": {
     "elapsed": 447,
     "status": "ok",
     "timestamp": 1670604428298,
     "user": {
      "displayName": "Fernando José Rendón Segador",
      "userId": "09288482551460164544"
     },
     "user_tz": -60
    },
    "id": "844W7YPn82Gw",
    "outputId": "ea88bcec-2ee8-4229-e43f-6c1a767fdc89",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You must install pydot (`pip install pydot`) and install graphviz (see instructions at https://graphviz.gitlab.io/download/) for plot_model to work.\n"
     ]
    }
   ],
   "source": [
    "tf.keras.utils.plot_model(model, \n",
    "                          show_shapes=True,\n",
    "                          show_dtype=True,\n",
    "                          show_layer_names=True,\n",
    "                          rankdir='LR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RjM9Xf2Ry-lq",
    "outputId": "3f4f80c6-a5ac-4e5e-8981-be5081cd7e3c",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n",
      "WARNING:tensorflow:From C:\\Users\\Fer_U\\PycharmProjects\\CyberattacksAttention\\venv\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Cannot perturb non-Tensor input: dict_keys(['label'])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9/9 [==============================] - 8s 403ms/step - loss: 0.9444 - sparse_categorical_crossentropy: 0.7739 - sparse_categorical_accuracy: 0.5595 - scaled_adversarial_loss: 0.1705 - val_loss: 0.7448 - val_sparse_categorical_crossentropy: 0.6004 - val_sparse_categorical_accuracy: 0.7062 - val_scaled_adversarial_loss: 0.1444\n",
      "Epoch 2/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.7171 - sparse_categorical_crossentropy: 0.5739 - sparse_categorical_accuracy: 0.7040 - scaled_adversarial_loss: 0.1432 - val_loss: 0.6775 - val_sparse_categorical_crossentropy: 0.5238 - val_sparse_categorical_accuracy: 0.8083 - val_scaled_adversarial_loss: 0.1537\n",
      "Epoch 3/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.6716 - sparse_categorical_crossentropy: 0.5312 - sparse_categorical_accuracy: 0.7355 - scaled_adversarial_loss: 0.1404 - val_loss: 0.6581 - val_sparse_categorical_crossentropy: 0.4988 - val_sparse_categorical_accuracy: 0.7938 - val_scaled_adversarial_loss: 0.1594\n",
      "Epoch 4/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.6675 - sparse_categorical_crossentropy: 0.5218 - sparse_categorical_accuracy: 0.7572 - scaled_adversarial_loss: 0.1458 - val_loss: 0.6294 - val_sparse_categorical_crossentropy: 0.4755 - val_sparse_categorical_accuracy: 0.8295 - val_scaled_adversarial_loss: 0.1539\n",
      "Epoch 5/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.6275 - sparse_categorical_crossentropy: 0.4829 - sparse_categorical_accuracy: 0.7842 - scaled_adversarial_loss: 0.1446 - val_loss: 0.6278 - val_sparse_categorical_crossentropy: 0.4786 - val_sparse_categorical_accuracy: 0.8237 - val_scaled_adversarial_loss: 0.1492\n",
      "Epoch 6/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.5995 - sparse_categorical_crossentropy: 0.4605 - sparse_categorical_accuracy: 0.7898 - scaled_adversarial_loss: 0.1390 - val_loss: 0.6063 - val_sparse_categorical_crossentropy: 0.4423 - val_sparse_categorical_accuracy: 0.8227 - val_scaled_adversarial_loss: 0.1640\n",
      "Epoch 7/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.6236 - sparse_categorical_crossentropy: 0.4830 - sparse_categorical_accuracy: 0.7876 - scaled_adversarial_loss: 0.1405 - val_loss: 0.5938 - val_sparse_categorical_crossentropy: 0.4323 - val_sparse_categorical_accuracy: 0.8179 - val_scaled_adversarial_loss: 0.1615\n",
      "Epoch 8/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.5983 - sparse_categorical_crossentropy: 0.4581 - sparse_categorical_accuracy: 0.8018 - scaled_adversarial_loss: 0.1402 - val_loss: 0.5849 - val_sparse_categorical_crossentropy: 0.4316 - val_sparse_categorical_accuracy: 0.8459 - val_scaled_adversarial_loss: 0.1532\n",
      "Epoch 9/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.5850 - sparse_categorical_crossentropy: 0.4407 - sparse_categorical_accuracy: 0.8006 - scaled_adversarial_loss: 0.1443 - val_loss: 0.6068 - val_sparse_categorical_crossentropy: 0.4595 - val_sparse_categorical_accuracy: 0.8333 - val_scaled_adversarial_loss: 0.1474\n",
      "Epoch 10/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5858 - sparse_categorical_crossentropy: 0.4398 - sparse_categorical_accuracy: 0.8103 - scaled_adversarial_loss: 0.1460 - val_loss: 0.5863 - val_sparse_categorical_crossentropy: 0.4383 - val_sparse_categorical_accuracy: 0.8459 - val_scaled_adversarial_loss: 0.1480\n",
      "Epoch 11/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5564 - sparse_categorical_crossentropy: 0.4175 - sparse_categorical_accuracy: 0.8151 - scaled_adversarial_loss: 0.1389 - val_loss: 0.5765 - val_sparse_categorical_crossentropy: 0.3884 - val_sparse_categorical_accuracy: 0.8584 - val_scaled_adversarial_loss: 0.1881\n",
      "Epoch 12/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.5843 - sparse_categorical_crossentropy: 0.4344 - sparse_categorical_accuracy: 0.8170 - scaled_adversarial_loss: 0.1499 - val_loss: 0.5767 - val_sparse_categorical_crossentropy: 0.4120 - val_sparse_categorical_accuracy: 0.8353 - val_scaled_adversarial_loss: 0.1647\n",
      "Epoch 13/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5734 - sparse_categorical_crossentropy: 0.4266 - sparse_categorical_accuracy: 0.8271 - scaled_adversarial_loss: 0.1468 - val_loss: 0.5616 - val_sparse_categorical_crossentropy: 0.4003 - val_sparse_categorical_accuracy: 0.8487 - val_scaled_adversarial_loss: 0.1613\n",
      "Epoch 14/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.5535 - sparse_categorical_crossentropy: 0.4090 - sparse_categorical_accuracy: 0.8276 - scaled_adversarial_loss: 0.1445 - val_loss: 0.5526 - val_sparse_categorical_crossentropy: 0.3902 - val_sparse_categorical_accuracy: 0.8449 - val_scaled_adversarial_loss: 0.1624\n",
      "Epoch 15/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.5503 - sparse_categorical_crossentropy: 0.4088 - sparse_categorical_accuracy: 0.8211 - scaled_adversarial_loss: 0.1414 - val_loss: 0.5648 - val_sparse_categorical_crossentropy: 0.3763 - val_sparse_categorical_accuracy: 0.8439 - val_scaled_adversarial_loss: 0.1885\n",
      "Epoch 16/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.5743 - sparse_categorical_crossentropy: 0.4201 - sparse_categorical_accuracy: 0.8339 - scaled_adversarial_loss: 0.1543 - val_loss: 0.5564 - val_sparse_categorical_crossentropy: 0.3978 - val_sparse_categorical_accuracy: 0.8593 - val_scaled_adversarial_loss: 0.1586\n",
      "Epoch 17/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.5560 - sparse_categorical_crossentropy: 0.4031 - sparse_categorical_accuracy: 0.8324 - scaled_adversarial_loss: 0.1529 - val_loss: 0.5772 - val_sparse_categorical_crossentropy: 0.4281 - val_sparse_categorical_accuracy: 0.8632 - val_scaled_adversarial_loss: 0.1491\n",
      "Epoch 18/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5590 - sparse_categorical_crossentropy: 0.4085 - sparse_categorical_accuracy: 0.8327 - scaled_adversarial_loss: 0.1505 - val_loss: 0.5560 - val_sparse_categorical_crossentropy: 0.4014 - val_sparse_categorical_accuracy: 0.8516 - val_scaled_adversarial_loss: 0.1546\n",
      "Epoch 19/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5671 - sparse_categorical_crossentropy: 0.4119 - sparse_categorical_accuracy: 0.8305 - scaled_adversarial_loss: 0.1552 - val_loss: 0.5486 - val_sparse_categorical_crossentropy: 0.3852 - val_sparse_categorical_accuracy: 0.8555 - val_scaled_adversarial_loss: 0.1634\n",
      "Epoch 20/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.5722 - sparse_categorical_crossentropy: 0.4176 - sparse_categorical_accuracy: 0.8341 - scaled_adversarial_loss: 0.1546 - val_loss: 0.5465 - val_sparse_categorical_crossentropy: 0.3800 - val_sparse_categorical_accuracy: 0.8497 - val_scaled_adversarial_loss: 0.1665\n",
      "Epoch 21/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.5562 - sparse_categorical_crossentropy: 0.4034 - sparse_categorical_accuracy: 0.8341 - scaled_adversarial_loss: 0.1529 - val_loss: 0.5428 - val_sparse_categorical_crossentropy: 0.3617 - val_sparse_categorical_accuracy: 0.8507 - val_scaled_adversarial_loss: 0.1812\n",
      "Epoch 22/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5707 - sparse_categorical_crossentropy: 0.4145 - sparse_categorical_accuracy: 0.8414 - scaled_adversarial_loss: 0.1562 - val_loss: 0.5425 - val_sparse_categorical_crossentropy: 0.3680 - val_sparse_categorical_accuracy: 0.8690 - val_scaled_adversarial_loss: 0.1746\n",
      "Epoch 23/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5422 - sparse_categorical_crossentropy: 0.3882 - sparse_categorical_accuracy: 0.8443 - scaled_adversarial_loss: 0.1540 - val_loss: 0.5382 - val_sparse_categorical_crossentropy: 0.3564 - val_sparse_categorical_accuracy: 0.8526 - val_scaled_adversarial_loss: 0.1818\n",
      "Epoch 24/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5276 - sparse_categorical_crossentropy: 0.3785 - sparse_categorical_accuracy: 0.8411 - scaled_adversarial_loss: 0.1491 - val_loss: 0.5359 - val_sparse_categorical_crossentropy: 0.3442 - val_sparse_categorical_accuracy: 0.8545 - val_scaled_adversarial_loss: 0.1918\n",
      "Epoch 25/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5629 - sparse_categorical_crossentropy: 0.4042 - sparse_categorical_accuracy: 0.8358 - scaled_adversarial_loss: 0.1587 - val_loss: 0.5312 - val_sparse_categorical_crossentropy: 0.3490 - val_sparse_categorical_accuracy: 0.8584 - val_scaled_adversarial_loss: 0.1822\n",
      "Epoch 26/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5400 - sparse_categorical_crossentropy: 0.3815 - sparse_categorical_accuracy: 0.8484 - scaled_adversarial_loss: 0.1585 - val_loss: 0.5369 - val_sparse_categorical_crossentropy: 0.3649 - val_sparse_categorical_accuracy: 0.8661 - val_scaled_adversarial_loss: 0.1719\n",
      "Epoch 27/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.5355 - sparse_categorical_crossentropy: 0.3760 - sparse_categorical_accuracy: 0.8496 - scaled_adversarial_loss: 0.1595 - val_loss: 0.5572 - val_sparse_categorical_crossentropy: 0.3945 - val_sparse_categorical_accuracy: 0.8613 - val_scaled_adversarial_loss: 0.1627\n",
      "Epoch 28/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5411 - sparse_categorical_crossentropy: 0.3795 - sparse_categorical_accuracy: 0.8428 - scaled_adversarial_loss: 0.1616 - val_loss: 0.5364 - val_sparse_categorical_crossentropy: 0.3587 - val_sparse_categorical_accuracy: 0.8565 - val_scaled_adversarial_loss: 0.1777\n",
      "Epoch 29/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.5498 - sparse_categorical_crossentropy: 0.3903 - sparse_categorical_accuracy: 0.8365 - scaled_adversarial_loss: 0.1594 - val_loss: 0.5594 - val_sparse_categorical_crossentropy: 0.3909 - val_sparse_categorical_accuracy: 0.8622 - val_scaled_adversarial_loss: 0.1685\n",
      "Epoch 30/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5524 - sparse_categorical_crossentropy: 0.3962 - sparse_categorical_accuracy: 0.8431 - scaled_adversarial_loss: 0.1562 - val_loss: 0.5372 - val_sparse_categorical_crossentropy: 0.3630 - val_sparse_categorical_accuracy: 0.8593 - val_scaled_adversarial_loss: 0.1742\n",
      "Epoch 31/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.5431 - sparse_categorical_crossentropy: 0.3825 - sparse_categorical_accuracy: 0.8525 - scaled_adversarial_loss: 0.1606 - val_loss: 0.5343 - val_sparse_categorical_crossentropy: 0.3483 - val_sparse_categorical_accuracy: 0.8536 - val_scaled_adversarial_loss: 0.1859\n",
      "Epoch 32/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5456 - sparse_categorical_crossentropy: 0.3867 - sparse_categorical_accuracy: 0.8435 - scaled_adversarial_loss: 0.1589 - val_loss: 0.5296 - val_sparse_categorical_crossentropy: 0.3444 - val_sparse_categorical_accuracy: 0.8690 - val_scaled_adversarial_loss: 0.1852\n",
      "Epoch 33/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5160 - sparse_categorical_crossentropy: 0.3556 - sparse_categorical_accuracy: 0.8515 - scaled_adversarial_loss: 0.1604 - val_loss: 0.5350 - val_sparse_categorical_crossentropy: 0.3396 - val_sparse_categorical_accuracy: 0.8709 - val_scaled_adversarial_loss: 0.1954\n",
      "Epoch 34/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.5407 - sparse_categorical_crossentropy: 0.3782 - sparse_categorical_accuracy: 0.8515 - scaled_adversarial_loss: 0.1625 - val_loss: 0.5503 - val_sparse_categorical_crossentropy: 0.3654 - val_sparse_categorical_accuracy: 0.8565 - val_scaled_adversarial_loss: 0.1849\n",
      "Epoch 35/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5330 - sparse_categorical_crossentropy: 0.3738 - sparse_categorical_accuracy: 0.8464 - scaled_adversarial_loss: 0.1592 - val_loss: 0.5360 - val_sparse_categorical_crossentropy: 0.3609 - val_sparse_categorical_accuracy: 0.8671 - val_scaled_adversarial_loss: 0.1751\n",
      "Epoch 36/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.5337 - sparse_categorical_crossentropy: 0.3740 - sparse_categorical_accuracy: 0.8513 - scaled_adversarial_loss: 0.1597 - val_loss: 0.5397 - val_sparse_categorical_crossentropy: 0.3690 - val_sparse_categorical_accuracy: 0.8613 - val_scaled_adversarial_loss: 0.1707\n",
      "Epoch 37/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5211 - sparse_categorical_crossentropy: 0.3602 - sparse_categorical_accuracy: 0.8527 - scaled_adversarial_loss: 0.1609 - val_loss: 0.5295 - val_sparse_categorical_crossentropy: 0.3436 - val_sparse_categorical_accuracy: 0.8622 - val_scaled_adversarial_loss: 0.1859\n",
      "Epoch 38/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.5132 - sparse_categorical_crossentropy: 0.3508 - sparse_categorical_accuracy: 0.8582 - scaled_adversarial_loss: 0.1624 - val_loss: 0.5291 - val_sparse_categorical_crossentropy: 0.3453 - val_sparse_categorical_accuracy: 0.8661 - val_scaled_adversarial_loss: 0.1839\n",
      "Epoch 39/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.5459 - sparse_categorical_crossentropy: 0.3789 - sparse_categorical_accuracy: 0.8481 - scaled_adversarial_loss: 0.1670 - val_loss: 0.5341 - val_sparse_categorical_crossentropy: 0.3601 - val_sparse_categorical_accuracy: 0.8680 - val_scaled_adversarial_loss: 0.1740\n",
      "Epoch 40/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5482 - sparse_categorical_crossentropy: 0.3829 - sparse_categorical_accuracy: 0.8510 - scaled_adversarial_loss: 0.1653 - val_loss: 0.5459 - val_sparse_categorical_crossentropy: 0.3640 - val_sparse_categorical_accuracy: 0.8555 - val_scaled_adversarial_loss: 0.1820\n",
      "Epoch 41/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.5182 - sparse_categorical_crossentropy: 0.3601 - sparse_categorical_accuracy: 0.8491 - scaled_adversarial_loss: 0.1581 - val_loss: 0.5331 - val_sparse_categorical_crossentropy: 0.3435 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1896\n",
      "Epoch 42/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.5142 - sparse_categorical_crossentropy: 0.3583 - sparse_categorical_accuracy: 0.8527 - scaled_adversarial_loss: 0.1559 - val_loss: 0.5570 - val_sparse_categorical_crossentropy: 0.3426 - val_sparse_categorical_accuracy: 0.8593 - val_scaled_adversarial_loss: 0.2144\n",
      "Epoch 43/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.5573 - sparse_categorical_crossentropy: 0.3930 - sparse_categorical_accuracy: 0.8556 - scaled_adversarial_loss: 0.1643 - val_loss: 0.5329 - val_sparse_categorical_crossentropy: 0.3603 - val_sparse_categorical_accuracy: 0.8622 - val_scaled_adversarial_loss: 0.1726\n",
      "Epoch 44/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.5273 - sparse_categorical_crossentropy: 0.3591 - sparse_categorical_accuracy: 0.8558 - scaled_adversarial_loss: 0.1682 - val_loss: 0.5397 - val_sparse_categorical_crossentropy: 0.3716 - val_sparse_categorical_accuracy: 0.8680 - val_scaled_adversarial_loss: 0.1681\n",
      "Epoch 45/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.5206 - sparse_categorical_crossentropy: 0.3607 - sparse_categorical_accuracy: 0.8505 - scaled_adversarial_loss: 0.1599 - val_loss: 0.5321 - val_sparse_categorical_crossentropy: 0.3582 - val_sparse_categorical_accuracy: 0.8671 - val_scaled_adversarial_loss: 0.1739\n",
      "Epoch 46/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.5373 - sparse_categorical_crossentropy: 0.3662 - sparse_categorical_accuracy: 0.8527 - scaled_adversarial_loss: 0.1711 - val_loss: 0.5443 - val_sparse_categorical_crossentropy: 0.3787 - val_sparse_categorical_accuracy: 0.8613 - val_scaled_adversarial_loss: 0.1656\n",
      "Epoch 47/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.5207 - sparse_categorical_crossentropy: 0.3609 - sparse_categorical_accuracy: 0.8546 - scaled_adversarial_loss: 0.1599 - val_loss: 0.5329 - val_sparse_categorical_crossentropy: 0.3358 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1971\n",
      "Epoch 48/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.5331 - sparse_categorical_crossentropy: 0.3697 - sparse_categorical_accuracy: 0.8575 - scaled_adversarial_loss: 0.1634 - val_loss: 0.5269 - val_sparse_categorical_crossentropy: 0.3371 - val_sparse_categorical_accuracy: 0.8680 - val_scaled_adversarial_loss: 0.1898\n",
      "Epoch 49/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5287 - sparse_categorical_crossentropy: 0.3653 - sparse_categorical_accuracy: 0.8525 - scaled_adversarial_loss: 0.1634 - val_loss: 0.5313 - val_sparse_categorical_crossentropy: 0.3565 - val_sparse_categorical_accuracy: 0.8690 - val_scaled_adversarial_loss: 0.1748\n",
      "Epoch 50/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.5433 - sparse_categorical_crossentropy: 0.3806 - sparse_categorical_accuracy: 0.8558 - scaled_adversarial_loss: 0.1627 - val_loss: 0.5628 - val_sparse_categorical_crossentropy: 0.3964 - val_sparse_categorical_accuracy: 0.8536 - val_scaled_adversarial_loss: 0.1664\n",
      "Epoch 51/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.5311 - sparse_categorical_crossentropy: 0.3678 - sparse_categorical_accuracy: 0.8452 - scaled_adversarial_loss: 0.1633 - val_loss: 0.5344 - val_sparse_categorical_crossentropy: 0.3649 - val_sparse_categorical_accuracy: 0.8709 - val_scaled_adversarial_loss: 0.1695\n",
      "Epoch 52/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5291 - sparse_categorical_crossentropy: 0.3673 - sparse_categorical_accuracy: 0.8505 - scaled_adversarial_loss: 0.1618 - val_loss: 0.5304 - val_sparse_categorical_crossentropy: 0.3558 - val_sparse_categorical_accuracy: 0.8709 - val_scaled_adversarial_loss: 0.1746\n",
      "Epoch 53/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.5159 - sparse_categorical_crossentropy: 0.3512 - sparse_categorical_accuracy: 0.8573 - scaled_adversarial_loss: 0.1648 - val_loss: 0.5369 - val_sparse_categorical_crossentropy: 0.3661 - val_sparse_categorical_accuracy: 0.8728 - val_scaled_adversarial_loss: 0.1708\n",
      "Epoch 54/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5421 - sparse_categorical_crossentropy: 0.3714 - sparse_categorical_accuracy: 0.8554 - scaled_adversarial_loss: 0.1707 - val_loss: 0.5304 - val_sparse_categorical_crossentropy: 0.3553 - val_sparse_categorical_accuracy: 0.8728 - val_scaled_adversarial_loss: 0.1752\n",
      "Epoch 55/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5210 - sparse_categorical_crossentropy: 0.3546 - sparse_categorical_accuracy: 0.8602 - scaled_adversarial_loss: 0.1664 - val_loss: 0.5262 - val_sparse_categorical_crossentropy: 0.3385 - val_sparse_categorical_accuracy: 0.8748 - val_scaled_adversarial_loss: 0.1876\n",
      "Epoch 56/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5315 - sparse_categorical_crossentropy: 0.3650 - sparse_categorical_accuracy: 0.8602 - scaled_adversarial_loss: 0.1665 - val_loss: 0.5337 - val_sparse_categorical_crossentropy: 0.3593 - val_sparse_categorical_accuracy: 0.8709 - val_scaled_adversarial_loss: 0.1744\n",
      "Epoch 57/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5248 - sparse_categorical_crossentropy: 0.3584 - sparse_categorical_accuracy: 0.8554 - scaled_adversarial_loss: 0.1663 - val_loss: 0.5333 - val_sparse_categorical_crossentropy: 0.3576 - val_sparse_categorical_accuracy: 0.8709 - val_scaled_adversarial_loss: 0.1757\n",
      "Epoch 58/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.5331 - sparse_categorical_crossentropy: 0.3648 - sparse_categorical_accuracy: 0.8534 - scaled_adversarial_loss: 0.1683 - val_loss: 0.5297 - val_sparse_categorical_crossentropy: 0.3463 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1834\n",
      "Epoch 59/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5177 - sparse_categorical_crossentropy: 0.3516 - sparse_categorical_accuracy: 0.8602 - scaled_adversarial_loss: 0.1662 - val_loss: 0.5346 - val_sparse_categorical_crossentropy: 0.3455 - val_sparse_categorical_accuracy: 0.8622 - val_scaled_adversarial_loss: 0.1890\n",
      "Epoch 60/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.5290 - sparse_categorical_crossentropy: 0.3609 - sparse_categorical_accuracy: 0.8570 - scaled_adversarial_loss: 0.1681 - val_loss: 0.5370 - val_sparse_categorical_crossentropy: 0.3604 - val_sparse_categorical_accuracy: 0.8613 - val_scaled_adversarial_loss: 0.1767\n",
      "Epoch 61/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.5121 - sparse_categorical_crossentropy: 0.3533 - sparse_categorical_accuracy: 0.8476 - scaled_adversarial_loss: 0.1588 - val_loss: 0.5285 - val_sparse_categorical_crossentropy: 0.3398 - val_sparse_categorical_accuracy: 0.8690 - val_scaled_adversarial_loss: 0.1887\n",
      "Epoch 62/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5385 - sparse_categorical_crossentropy: 0.3710 - sparse_categorical_accuracy: 0.8525 - scaled_adversarial_loss: 0.1675 - val_loss: 0.5391 - val_sparse_categorical_crossentropy: 0.3583 - val_sparse_categorical_accuracy: 0.8680 - val_scaled_adversarial_loss: 0.1808\n",
      "Epoch 63/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5345 - sparse_categorical_crossentropy: 0.3661 - sparse_categorical_accuracy: 0.8551 - scaled_adversarial_loss: 0.1685 - val_loss: 0.5480 - val_sparse_categorical_crossentropy: 0.3808 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1672\n",
      "Epoch 64/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.5342 - sparse_categorical_crossentropy: 0.3623 - sparse_categorical_accuracy: 0.8520 - scaled_adversarial_loss: 0.1718 - val_loss: 0.5286 - val_sparse_categorical_crossentropy: 0.3487 - val_sparse_categorical_accuracy: 0.8709 - val_scaled_adversarial_loss: 0.1799\n",
      "Epoch 65/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.5262 - sparse_categorical_crossentropy: 0.3647 - sparse_categorical_accuracy: 0.8578 - scaled_adversarial_loss: 0.1614 - val_loss: 0.5361 - val_sparse_categorical_crossentropy: 0.3399 - val_sparse_categorical_accuracy: 0.8622 - val_scaled_adversarial_loss: 0.1962\n",
      "Epoch 66/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.5303 - sparse_categorical_crossentropy: 0.3618 - sparse_categorical_accuracy: 0.8602 - scaled_adversarial_loss: 0.1685 - val_loss: 0.5304 - val_sparse_categorical_crossentropy: 0.3421 - val_sparse_categorical_accuracy: 0.8699 - val_scaled_adversarial_loss: 0.1883\n",
      "Epoch 67/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.5342 - sparse_categorical_crossentropy: 0.3696 - sparse_categorical_accuracy: 0.8534 - scaled_adversarial_loss: 0.1646 - val_loss: 0.5307 - val_sparse_categorical_crossentropy: 0.3534 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1773\n",
      "Epoch 68/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.5297 - sparse_categorical_crossentropy: 0.3621 - sparse_categorical_accuracy: 0.8597 - scaled_adversarial_loss: 0.1677 - val_loss: 0.5372 - val_sparse_categorical_crossentropy: 0.3696 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1675\n",
      "Epoch 69/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5305 - sparse_categorical_crossentropy: 0.3608 - sparse_categorical_accuracy: 0.8631 - scaled_adversarial_loss: 0.1697 - val_loss: 0.5562 - val_sparse_categorical_crossentropy: 0.3923 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1639\n",
      "Epoch 70/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.5343 - sparse_categorical_crossentropy: 0.3643 - sparse_categorical_accuracy: 0.8602 - scaled_adversarial_loss: 0.1699 - val_loss: 0.5301 - val_sparse_categorical_crossentropy: 0.3557 - val_sparse_categorical_accuracy: 0.8748 - val_scaled_adversarial_loss: 0.1745\n",
      "Epoch 71/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.5313 - sparse_categorical_crossentropy: 0.3618 - sparse_categorical_accuracy: 0.8628 - scaled_adversarial_loss: 0.1694 - val_loss: 0.5278 - val_sparse_categorical_crossentropy: 0.3547 - val_sparse_categorical_accuracy: 0.8728 - val_scaled_adversarial_loss: 0.1731\n",
      "Epoch 72/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.5440 - sparse_categorical_crossentropy: 0.3748 - sparse_categorical_accuracy: 0.8602 - scaled_adversarial_loss: 0.1691 - val_loss: 0.5179 - val_sparse_categorical_crossentropy: 0.3339 - val_sparse_categorical_accuracy: 0.8748 - val_scaled_adversarial_loss: 0.1840\n",
      "Epoch 73/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.5363 - sparse_categorical_crossentropy: 0.3666 - sparse_categorical_accuracy: 0.8595 - scaled_adversarial_loss: 0.1697 - val_loss: 0.5168 - val_sparse_categorical_crossentropy: 0.3418 - val_sparse_categorical_accuracy: 0.8738 - val_scaled_adversarial_loss: 0.1750\n",
      "Epoch 74/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.5317 - sparse_categorical_crossentropy: 0.3632 - sparse_categorical_accuracy: 0.8655 - scaled_adversarial_loss: 0.1684 - val_loss: 0.5254 - val_sparse_categorical_crossentropy: 0.3212 - val_sparse_categorical_accuracy: 0.8748 - val_scaled_adversarial_loss: 0.2041\n",
      "Epoch 75/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5249 - sparse_categorical_crossentropy: 0.3619 - sparse_categorical_accuracy: 0.8599 - scaled_adversarial_loss: 0.1630 - val_loss: 0.5151 - val_sparse_categorical_crossentropy: 0.3176 - val_sparse_categorical_accuracy: 0.8738 - val_scaled_adversarial_loss: 0.1975\n",
      "Epoch 76/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.5047 - sparse_categorical_crossentropy: 0.3377 - sparse_categorical_accuracy: 0.8614 - scaled_adversarial_loss: 0.1670 - val_loss: 0.5142 - val_sparse_categorical_crossentropy: 0.3138 - val_sparse_categorical_accuracy: 0.8757 - val_scaled_adversarial_loss: 0.2004\n",
      "Epoch 77/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.5183 - sparse_categorical_crossentropy: 0.3496 - sparse_categorical_accuracy: 0.8645 - scaled_adversarial_loss: 0.1686 - val_loss: 0.5215 - val_sparse_categorical_crossentropy: 0.3280 - val_sparse_categorical_accuracy: 0.8728 - val_scaled_adversarial_loss: 0.1935\n",
      "Epoch 78/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.5188 - sparse_categorical_crossentropy: 0.3497 - sparse_categorical_accuracy: 0.8667 - scaled_adversarial_loss: 0.1691 - val_loss: 0.5219 - val_sparse_categorical_crossentropy: 0.3333 - val_sparse_categorical_accuracy: 0.8776 - val_scaled_adversarial_loss: 0.1886\n",
      "Epoch 79/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.5326 - sparse_categorical_crossentropy: 0.3609 - sparse_categorical_accuracy: 0.8611 - scaled_adversarial_loss: 0.1717 - val_loss: 0.5136 - val_sparse_categorical_crossentropy: 0.3348 - val_sparse_categorical_accuracy: 0.8748 - val_scaled_adversarial_loss: 0.1788\n",
      "Epoch 80/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.4984 - sparse_categorical_crossentropy: 0.3401 - sparse_categorical_accuracy: 0.8662 - scaled_adversarial_loss: 0.1583 - val_loss: 0.5180 - val_sparse_categorical_crossentropy: 0.3043 - val_sparse_categorical_accuracy: 0.8748 - val_scaled_adversarial_loss: 0.2137\n",
      "Epoch 81/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.4922 - sparse_categorical_crossentropy: 0.3302 - sparse_categorical_accuracy: 0.8662 - scaled_adversarial_loss: 0.1620 - val_loss: 0.5230 - val_sparse_categorical_crossentropy: 0.2999 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.2231\n",
      "Epoch 82/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.4945 - sparse_categorical_crossentropy: 0.3323 - sparse_categorical_accuracy: 0.8614 - scaled_adversarial_loss: 0.1622 - val_loss: 0.5127 - val_sparse_categorical_crossentropy: 0.3032 - val_sparse_categorical_accuracy: 0.8767 - val_scaled_adversarial_loss: 0.2095\n",
      "Epoch 83/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.5029 - sparse_categorical_crossentropy: 0.3353 - sparse_categorical_accuracy: 0.8623 - scaled_adversarial_loss: 0.1676 - val_loss: 0.5090 - val_sparse_categorical_crossentropy: 0.3155 - val_sparse_categorical_accuracy: 0.8719 - val_scaled_adversarial_loss: 0.1935\n",
      "Epoch 84/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.5082 - sparse_categorical_crossentropy: 0.3353 - sparse_categorical_accuracy: 0.8635 - scaled_adversarial_loss: 0.1729 - val_loss: 0.4981 - val_sparse_categorical_crossentropy: 0.3070 - val_sparse_categorical_accuracy: 0.8796 - val_scaled_adversarial_loss: 0.1911\n",
      "Epoch 85/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.4830 - sparse_categorical_crossentropy: 0.3170 - sparse_categorical_accuracy: 0.8672 - scaled_adversarial_loss: 0.1659 - val_loss: 0.5049 - val_sparse_categorical_crossentropy: 0.3215 - val_sparse_categorical_accuracy: 0.8786 - val_scaled_adversarial_loss: 0.1834\n",
      "Epoch 86/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.4781 - sparse_categorical_crossentropy: 0.3160 - sparse_categorical_accuracy: 0.8635 - scaled_adversarial_loss: 0.1621 - val_loss: 0.5039 - val_sparse_categorical_crossentropy: 0.3078 - val_sparse_categorical_accuracy: 0.8776 - val_scaled_adversarial_loss: 0.1961\n",
      "Epoch 87/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.4737 - sparse_categorical_crossentropy: 0.3066 - sparse_categorical_accuracy: 0.8734 - scaled_adversarial_loss: 0.1671 - val_loss: 0.5004 - val_sparse_categorical_crossentropy: 0.2894 - val_sparse_categorical_accuracy: 0.8825 - val_scaled_adversarial_loss: 0.2110\n",
      "Epoch 88/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.4908 - sparse_categorical_crossentropy: 0.3211 - sparse_categorical_accuracy: 0.8672 - scaled_adversarial_loss: 0.1697 - val_loss: 0.5034 - val_sparse_categorical_crossentropy: 0.3034 - val_sparse_categorical_accuracy: 0.8796 - val_scaled_adversarial_loss: 0.2000\n",
      "Epoch 89/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.4751 - sparse_categorical_crossentropy: 0.3068 - sparse_categorical_accuracy: 0.8715 - scaled_adversarial_loss: 0.1683 - val_loss: 0.5094 - val_sparse_categorical_crossentropy: 0.2969 - val_sparse_categorical_accuracy: 0.8796 - val_scaled_adversarial_loss: 0.2125\n",
      "Epoch 90/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.4830 - sparse_categorical_crossentropy: 0.3158 - sparse_categorical_accuracy: 0.8698 - scaled_adversarial_loss: 0.1672 - val_loss: 0.5065 - val_sparse_categorical_crossentropy: 0.3001 - val_sparse_categorical_accuracy: 0.8825 - val_scaled_adversarial_loss: 0.2064\n",
      "Epoch 91/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.4778 - sparse_categorical_crossentropy: 0.3074 - sparse_categorical_accuracy: 0.8652 - scaled_adversarial_loss: 0.1704 - val_loss: 0.5005 - val_sparse_categorical_crossentropy: 0.3071 - val_sparse_categorical_accuracy: 0.8825 - val_scaled_adversarial_loss: 0.1934\n",
      "Epoch 92/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.4816 - sparse_categorical_crossentropy: 0.3084 - sparse_categorical_accuracy: 0.8727 - scaled_adversarial_loss: 0.1732 - val_loss: 0.5035 - val_sparse_categorical_crossentropy: 0.3119 - val_sparse_categorical_accuracy: 0.8815 - val_scaled_adversarial_loss: 0.1917\n",
      "Epoch 93/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.4749 - sparse_categorical_crossentropy: 0.3039 - sparse_categorical_accuracy: 0.8732 - scaled_adversarial_loss: 0.1710 - val_loss: 0.4956 - val_sparse_categorical_crossentropy: 0.3099 - val_sparse_categorical_accuracy: 0.8805 - val_scaled_adversarial_loss: 0.1857\n",
      "Epoch 94/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.4655 - sparse_categorical_crossentropy: 0.3003 - sparse_categorical_accuracy: 0.8701 - scaled_adversarial_loss: 0.1652 - val_loss: 0.5162 - val_sparse_categorical_crossentropy: 0.3058 - val_sparse_categorical_accuracy: 0.8844 - val_scaled_adversarial_loss: 0.2104\n",
      "Epoch 95/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.4683 - sparse_categorical_crossentropy: 0.2939 - sparse_categorical_accuracy: 0.8746 - scaled_adversarial_loss: 0.1744 - val_loss: 0.5110 - val_sparse_categorical_crossentropy: 0.3214 - val_sparse_categorical_accuracy: 0.8834 - val_scaled_adversarial_loss: 0.1896\n",
      "Epoch 96/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.4734 - sparse_categorical_crossentropy: 0.3077 - sparse_categorical_accuracy: 0.8720 - scaled_adversarial_loss: 0.1657 - val_loss: 0.5042 - val_sparse_categorical_crossentropy: 0.3063 - val_sparse_categorical_accuracy: 0.8844 - val_scaled_adversarial_loss: 0.1980\n",
      "Epoch 97/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.4689 - sparse_categorical_crossentropy: 0.2943 - sparse_categorical_accuracy: 0.8802 - scaled_adversarial_loss: 0.1746 - val_loss: 0.5267 - val_sparse_categorical_crossentropy: 0.3258 - val_sparse_categorical_accuracy: 0.8854 - val_scaled_adversarial_loss: 0.2009\n",
      "Epoch 98/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.4631 - sparse_categorical_crossentropy: 0.2920 - sparse_categorical_accuracy: 0.8797 - scaled_adversarial_loss: 0.1711 - val_loss: 0.5076 - val_sparse_categorical_crossentropy: 0.3151 - val_sparse_categorical_accuracy: 0.8892 - val_scaled_adversarial_loss: 0.1925\n",
      "Epoch 99/1000\n",
      "9/9 [==============================] - 4s 396ms/step - loss: 0.4619 - sparse_categorical_crossentropy: 0.2822 - sparse_categorical_accuracy: 0.8780 - scaled_adversarial_loss: 0.1797 - val_loss: 0.5131 - val_sparse_categorical_crossentropy: 0.3132 - val_sparse_categorical_accuracy: 0.8882 - val_scaled_adversarial_loss: 0.1999\n",
      "Epoch 100/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.4624 - sparse_categorical_crossentropy: 0.2924 - sparse_categorical_accuracy: 0.8816 - scaled_adversarial_loss: 0.1700 - val_loss: 0.5304 - val_sparse_categorical_crossentropy: 0.3179 - val_sparse_categorical_accuracy: 0.8882 - val_scaled_adversarial_loss: 0.2125\n",
      "Epoch 101/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.4647 - sparse_categorical_crossentropy: 0.2919 - sparse_categorical_accuracy: 0.8744 - scaled_adversarial_loss: 0.1728 - val_loss: 0.5093 - val_sparse_categorical_crossentropy: 0.3003 - val_sparse_categorical_accuracy: 0.8854 - val_scaled_adversarial_loss: 0.2090\n",
      "Epoch 102/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.4683 - sparse_categorical_crossentropy: 0.2981 - sparse_categorical_accuracy: 0.8742 - scaled_adversarial_loss: 0.1702 - val_loss: 0.5501 - val_sparse_categorical_crossentropy: 0.3421 - val_sparse_categorical_accuracy: 0.8844 - val_scaled_adversarial_loss: 0.2080\n",
      "Epoch 103/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.4709 - sparse_categorical_crossentropy: 0.2990 - sparse_categorical_accuracy: 0.8780 - scaled_adversarial_loss: 0.1720 - val_loss: 0.5154 - val_sparse_categorical_crossentropy: 0.3265 - val_sparse_categorical_accuracy: 0.8854 - val_scaled_adversarial_loss: 0.1889\n",
      "Epoch 104/1000\n",
      "9/9 [==============================] - 3s 393ms/step - loss: 0.4551 - sparse_categorical_crossentropy: 0.2837 - sparse_categorical_accuracy: 0.8804 - scaled_adversarial_loss: 0.1714 - val_loss: 0.5287 - val_sparse_categorical_crossentropy: 0.3212 - val_sparse_categorical_accuracy: 0.8882 - val_scaled_adversarial_loss: 0.2075\n",
      "Epoch 105/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.4662 - sparse_categorical_crossentropy: 0.2899 - sparse_categorical_accuracy: 0.8783 - scaled_adversarial_loss: 0.1763 - val_loss: 0.4871 - val_sparse_categorical_crossentropy: 0.3035 - val_sparse_categorical_accuracy: 0.8921 - val_scaled_adversarial_loss: 0.1837\n",
      "Epoch 106/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.4724 - sparse_categorical_crossentropy: 0.2985 - sparse_categorical_accuracy: 0.8783 - scaled_adversarial_loss: 0.1739 - val_loss: 0.5007 - val_sparse_categorical_crossentropy: 0.3099 - val_sparse_categorical_accuracy: 0.8882 - val_scaled_adversarial_loss: 0.1908\n",
      "Epoch 107/1000\n",
      "9/9 [==============================] - 3s 392ms/step - loss: 0.4650 - sparse_categorical_crossentropy: 0.2906 - sparse_categorical_accuracy: 0.8773 - scaled_adversarial_loss: 0.1743 - val_loss: 0.5202 - val_sparse_categorical_crossentropy: 0.3227 - val_sparse_categorical_accuracy: 0.8960 - val_scaled_adversarial_loss: 0.1975\n",
      "Epoch 108/1000\n",
      "9/9 [==============================] - 3s 388ms/step - loss: 0.4544 - sparse_categorical_crossentropy: 0.2830 - sparse_categorical_accuracy: 0.8838 - scaled_adversarial_loss: 0.1714 - val_loss: 0.5111 - val_sparse_categorical_crossentropy: 0.2852 - val_sparse_categorical_accuracy: 0.8940 - val_scaled_adversarial_loss: 0.2259\n",
      "Epoch 109/1000\n",
      "9/9 [==============================] - 4s 403ms/step - loss: 0.4813 - sparse_categorical_crossentropy: 0.3001 - sparse_categorical_accuracy: 0.8807 - scaled_adversarial_loss: 0.1812 - val_loss: 0.4852 - val_sparse_categorical_crossentropy: 0.2754 - val_sparse_categorical_accuracy: 0.8911 - val_scaled_adversarial_loss: 0.2098\n",
      "Epoch 110/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.4579 - sparse_categorical_crossentropy: 0.2908 - sparse_categorical_accuracy: 0.8766 - scaled_adversarial_loss: 0.1671 - val_loss: 0.4906 - val_sparse_categorical_crossentropy: 0.2792 - val_sparse_categorical_accuracy: 0.8863 - val_scaled_adversarial_loss: 0.2114\n",
      "Epoch 111/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.4366 - sparse_categorical_crossentropy: 0.2727 - sparse_categorical_accuracy: 0.8828 - scaled_adversarial_loss: 0.1639 - val_loss: 0.5303 - val_sparse_categorical_crossentropy: 0.3080 - val_sparse_categorical_accuracy: 0.8873 - val_scaled_adversarial_loss: 0.2223\n",
      "Epoch 112/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.4416 - sparse_categorical_crossentropy: 0.2713 - sparse_categorical_accuracy: 0.8828 - scaled_adversarial_loss: 0.1703 - val_loss: 0.5309 - val_sparse_categorical_crossentropy: 0.2956 - val_sparse_categorical_accuracy: 0.8825 - val_scaled_adversarial_loss: 0.2353\n",
      "Epoch 113/1000\n",
      "9/9 [==============================] - 3s 381ms/step - loss: 0.4757 - sparse_categorical_crossentropy: 0.2946 - sparse_categorical_accuracy: 0.8821 - scaled_adversarial_loss: 0.1811 - val_loss: 0.4968 - val_sparse_categorical_crossentropy: 0.2940 - val_sparse_categorical_accuracy: 0.8882 - val_scaled_adversarial_loss: 0.2027\n",
      "Epoch 114/1000\n",
      "9/9 [==============================] - 4s 388ms/step - loss: 0.4481 - sparse_categorical_crossentropy: 0.2809 - sparse_categorical_accuracy: 0.8877 - scaled_adversarial_loss: 0.1672 - val_loss: 0.5007 - val_sparse_categorical_crossentropy: 0.2872 - val_sparse_categorical_accuracy: 0.8960 - val_scaled_adversarial_loss: 0.2135\n",
      "Epoch 115/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.4316 - sparse_categorical_crossentropy: 0.2647 - sparse_categorical_accuracy: 0.8915 - scaled_adversarial_loss: 0.1669 - val_loss: 0.4505 - val_sparse_categorical_crossentropy: 0.2695 - val_sparse_categorical_accuracy: 0.8988 - val_scaled_adversarial_loss: 0.1810\n",
      "Epoch 116/1000\n",
      "9/9 [==============================] - 4s 439ms/step - loss: 0.4462 - sparse_categorical_crossentropy: 0.2770 - sparse_categorical_accuracy: 0.8845 - scaled_adversarial_loss: 0.1692 - val_loss: 0.4770 - val_sparse_categorical_crossentropy: 0.2803 - val_sparse_categorical_accuracy: 0.8979 - val_scaled_adversarial_loss: 0.1966\n",
      "Epoch 117/1000\n",
      "9/9 [==============================] - 4s 412ms/step - loss: 0.4398 - sparse_categorical_crossentropy: 0.2665 - sparse_categorical_accuracy: 0.8850 - scaled_adversarial_loss: 0.1733 - val_loss: 0.4783 - val_sparse_categorical_crossentropy: 0.2581 - val_sparse_categorical_accuracy: 0.8979 - val_scaled_adversarial_loss: 0.2202\n",
      "Epoch 118/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.4405 - sparse_categorical_crossentropy: 0.2722 - sparse_categorical_accuracy: 0.8865 - scaled_adversarial_loss: 0.1684 - val_loss: 0.5108 - val_sparse_categorical_crossentropy: 0.2707 - val_sparse_categorical_accuracy: 0.8921 - val_scaled_adversarial_loss: 0.2401\n",
      "Epoch 119/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.4559 - sparse_categorical_crossentropy: 0.2779 - sparse_categorical_accuracy: 0.8905 - scaled_adversarial_loss: 0.1780 - val_loss: 0.4687 - val_sparse_categorical_crossentropy: 0.2351 - val_sparse_categorical_accuracy: 0.8911 - val_scaled_adversarial_loss: 0.2335\n",
      "Epoch 120/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.4329 - sparse_categorical_crossentropy: 0.2564 - sparse_categorical_accuracy: 0.8915 - scaled_adversarial_loss: 0.1766 - val_loss: 0.5050 - val_sparse_categorical_crossentropy: 0.2614 - val_sparse_categorical_accuracy: 0.8950 - val_scaled_adversarial_loss: 0.2436\n",
      "Epoch 121/1000\n",
      "9/9 [==============================] - 4s 415ms/step - loss: 0.4311 - sparse_categorical_crossentropy: 0.2620 - sparse_categorical_accuracy: 0.8942 - scaled_adversarial_loss: 0.1691 - val_loss: 0.4613 - val_sparse_categorical_crossentropy: 0.2256 - val_sparse_categorical_accuracy: 0.8988 - val_scaled_adversarial_loss: 0.2358\n",
      "Epoch 122/1000\n",
      "9/9 [==============================] - 3s 390ms/step - loss: 0.4539 - sparse_categorical_crossentropy: 0.2786 - sparse_categorical_accuracy: 0.8869 - scaled_adversarial_loss: 0.1753 - val_loss: 0.4701 - val_sparse_categorical_crossentropy: 0.2629 - val_sparse_categorical_accuracy: 0.9027 - val_scaled_adversarial_loss: 0.2073\n",
      "Epoch 123/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.4472 - sparse_categorical_crossentropy: 0.2689 - sparse_categorical_accuracy: 0.8884 - scaled_adversarial_loss: 0.1783 - val_loss: 0.4441 - val_sparse_categorical_crossentropy: 0.2461 - val_sparse_categorical_accuracy: 0.8940 - val_scaled_adversarial_loss: 0.1980\n",
      "Epoch 124/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.4206 - sparse_categorical_crossentropy: 0.2563 - sparse_categorical_accuracy: 0.8925 - scaled_adversarial_loss: 0.1643 - val_loss: 0.4774 - val_sparse_categorical_crossentropy: 0.2679 - val_sparse_categorical_accuracy: 0.8988 - val_scaled_adversarial_loss: 0.2095\n",
      "Epoch 125/1000\n",
      "9/9 [==============================] - 4s 397ms/step - loss: 0.4242 - sparse_categorical_crossentropy: 0.2516 - sparse_categorical_accuracy: 0.8946 - scaled_adversarial_loss: 0.1726 - val_loss: 0.4492 - val_sparse_categorical_crossentropy: 0.2532 - val_sparse_categorical_accuracy: 0.9046 - val_scaled_adversarial_loss: 0.1960\n",
      "Epoch 126/1000\n",
      "9/9 [==============================] - 4s 411ms/step - loss: 0.4175 - sparse_categorical_crossentropy: 0.2505 - sparse_categorical_accuracy: 0.8932 - scaled_adversarial_loss: 0.1671 - val_loss: 0.4595 - val_sparse_categorical_crossentropy: 0.2478 - val_sparse_categorical_accuracy: 0.8998 - val_scaled_adversarial_loss: 0.2117\n",
      "Epoch 127/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.4350 - sparse_categorical_crossentropy: 0.2630 - sparse_categorical_accuracy: 0.8869 - scaled_adversarial_loss: 0.1720 - val_loss: 0.4788 - val_sparse_categorical_crossentropy: 0.2589 - val_sparse_categorical_accuracy: 0.8960 - val_scaled_adversarial_loss: 0.2198\n",
      "Epoch 128/1000\n",
      "9/9 [==============================] - 3s 389ms/step - loss: 0.4337 - sparse_categorical_crossentropy: 0.2618 - sparse_categorical_accuracy: 0.8927 - scaled_adversarial_loss: 0.1719 - val_loss: 0.4245 - val_sparse_categorical_crossentropy: 0.2212 - val_sparse_categorical_accuracy: 0.8988 - val_scaled_adversarial_loss: 0.2033\n",
      "Epoch 129/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.4175 - sparse_categorical_crossentropy: 0.2455 - sparse_categorical_accuracy: 0.8913 - scaled_adversarial_loss: 0.1720 - val_loss: 0.4345 - val_sparse_categorical_crossentropy: 0.2226 - val_sparse_categorical_accuracy: 0.9066 - val_scaled_adversarial_loss: 0.2119\n",
      "Epoch 130/1000\n",
      "9/9 [==============================] - 4s 439ms/step - loss: 0.4221 - sparse_categorical_crossentropy: 0.2548 - sparse_categorical_accuracy: 0.8905 - scaled_adversarial_loss: 0.1673 - val_loss: 0.4480 - val_sparse_categorical_crossentropy: 0.2300 - val_sparse_categorical_accuracy: 0.9046 - val_scaled_adversarial_loss: 0.2180\n",
      "Epoch 131/1000\n",
      "9/9 [==============================] - 4s 389ms/step - loss: 0.4208 - sparse_categorical_crossentropy: 0.2450 - sparse_categorical_accuracy: 0.9012 - scaled_adversarial_loss: 0.1758 - val_loss: 0.4585 - val_sparse_categorical_crossentropy: 0.2680 - val_sparse_categorical_accuracy: 0.9085 - val_scaled_adversarial_loss: 0.1905\n",
      "Epoch 132/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.4201 - sparse_categorical_crossentropy: 0.2505 - sparse_categorical_accuracy: 0.8987 - scaled_adversarial_loss: 0.1696 - val_loss: 0.4295 - val_sparse_categorical_crossentropy: 0.2311 - val_sparse_categorical_accuracy: 0.9123 - val_scaled_adversarial_loss: 0.1984\n",
      "Epoch 133/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.4257 - sparse_categorical_crossentropy: 0.2537 - sparse_categorical_accuracy: 0.9002 - scaled_adversarial_loss: 0.1719 - val_loss: 0.4332 - val_sparse_categorical_crossentropy: 0.2513 - val_sparse_categorical_accuracy: 0.9075 - val_scaled_adversarial_loss: 0.1819\n",
      "Epoch 134/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.3980 - sparse_categorical_crossentropy: 0.2362 - sparse_categorical_accuracy: 0.9009 - scaled_adversarial_loss: 0.1618 - val_loss: 0.4280 - val_sparse_categorical_crossentropy: 0.2103 - val_sparse_categorical_accuracy: 0.9123 - val_scaled_adversarial_loss: 0.2177\n",
      "Epoch 135/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.4147 - sparse_categorical_crossentropy: 0.2464 - sparse_categorical_accuracy: 0.9038 - scaled_adversarial_loss: 0.1683 - val_loss: 0.4376 - val_sparse_categorical_crossentropy: 0.2468 - val_sparse_categorical_accuracy: 0.9104 - val_scaled_adversarial_loss: 0.1908\n",
      "Epoch 136/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.4117 - sparse_categorical_crossentropy: 0.2477 - sparse_categorical_accuracy: 0.8987 - scaled_adversarial_loss: 0.1640 - val_loss: 0.4728 - val_sparse_categorical_crossentropy: 0.2678 - val_sparse_categorical_accuracy: 0.9075 - val_scaled_adversarial_loss: 0.2050\n",
      "Epoch 137/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.4074 - sparse_categorical_crossentropy: 0.2422 - sparse_categorical_accuracy: 0.9007 - scaled_adversarial_loss: 0.1653 - val_loss: 0.4552 - val_sparse_categorical_crossentropy: 0.2612 - val_sparse_categorical_accuracy: 0.9085 - val_scaled_adversarial_loss: 0.1940\n",
      "Epoch 138/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.3923 - sparse_categorical_crossentropy: 0.2246 - sparse_categorical_accuracy: 0.9028 - scaled_adversarial_loss: 0.1678 - val_loss: 0.4276 - val_sparse_categorical_crossentropy: 0.2392 - val_sparse_categorical_accuracy: 0.9191 - val_scaled_adversarial_loss: 0.1883\n",
      "Epoch 139/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.3921 - sparse_categorical_crossentropy: 0.2266 - sparse_categorical_accuracy: 0.9012 - scaled_adversarial_loss: 0.1655 - val_loss: 0.4060 - val_sparse_categorical_crossentropy: 0.2096 - val_sparse_categorical_accuracy: 0.9056 - val_scaled_adversarial_loss: 0.1964\n",
      "Epoch 140/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.4084 - sparse_categorical_crossentropy: 0.2473 - sparse_categorical_accuracy: 0.8920 - scaled_adversarial_loss: 0.1612 - val_loss: 0.4006 - val_sparse_categorical_crossentropy: 0.1911 - val_sparse_categorical_accuracy: 0.9162 - val_scaled_adversarial_loss: 0.2096\n",
      "Epoch 141/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.4150 - sparse_categorical_crossentropy: 0.2520 - sparse_categorical_accuracy: 0.8922 - scaled_adversarial_loss: 0.1630 - val_loss: 0.4096 - val_sparse_categorical_crossentropy: 0.2410 - val_sparse_categorical_accuracy: 0.9075 - val_scaled_adversarial_loss: 0.1686\n",
      "Epoch 142/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.4059 - sparse_categorical_crossentropy: 0.2408 - sparse_categorical_accuracy: 0.9062 - scaled_adversarial_loss: 0.1652 - val_loss: 0.4084 - val_sparse_categorical_crossentropy: 0.2528 - val_sparse_categorical_accuracy: 0.9066 - val_scaled_adversarial_loss: 0.1556\n",
      "Epoch 143/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.3925 - sparse_categorical_crossentropy: 0.2334 - sparse_categorical_accuracy: 0.9041 - scaled_adversarial_loss: 0.1592 - val_loss: 0.4057 - val_sparse_categorical_crossentropy: 0.2345 - val_sparse_categorical_accuracy: 0.9191 - val_scaled_adversarial_loss: 0.1712\n",
      "Epoch 144/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.3901 - sparse_categorical_crossentropy: 0.2249 - sparse_categorical_accuracy: 0.9125 - scaled_adversarial_loss: 0.1653 - val_loss: 0.3858 - val_sparse_categorical_crossentropy: 0.2045 - val_sparse_categorical_accuracy: 0.9200 - val_scaled_adversarial_loss: 0.1813\n",
      "Epoch 145/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.3811 - sparse_categorical_crossentropy: 0.2174 - sparse_categorical_accuracy: 0.9094 - scaled_adversarial_loss: 0.1637 - val_loss: 0.4003 - val_sparse_categorical_crossentropy: 0.2451 - val_sparse_categorical_accuracy: 0.9229 - val_scaled_adversarial_loss: 0.1552\n",
      "Epoch 146/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.3814 - sparse_categorical_crossentropy: 0.2233 - sparse_categorical_accuracy: 0.9115 - scaled_adversarial_loss: 0.1582 - val_loss: 0.3860 - val_sparse_categorical_crossentropy: 0.2131 - val_sparse_categorical_accuracy: 0.9306 - val_scaled_adversarial_loss: 0.1729\n",
      "Epoch 147/1000\n",
      "9/9 [==============================] - 4s 405ms/step - loss: 0.3848 - sparse_categorical_crossentropy: 0.2224 - sparse_categorical_accuracy: 0.9079 - scaled_adversarial_loss: 0.1624 - val_loss: 0.3837 - val_sparse_categorical_crossentropy: 0.2057 - val_sparse_categorical_accuracy: 0.9277 - val_scaled_adversarial_loss: 0.1781\n",
      "Epoch 148/1000\n",
      "9/9 [==============================] - 3s 385ms/step - loss: 0.3864 - sparse_categorical_crossentropy: 0.2148 - sparse_categorical_accuracy: 0.9147 - scaled_adversarial_loss: 0.1716 - val_loss: 0.3902 - val_sparse_categorical_crossentropy: 0.2251 - val_sparse_categorical_accuracy: 0.9345 - val_scaled_adversarial_loss: 0.1650\n",
      "Epoch 149/1000\n",
      "9/9 [==============================] - 4s 378ms/step - loss: 0.3761 - sparse_categorical_crossentropy: 0.2142 - sparse_categorical_accuracy: 0.9159 - scaled_adversarial_loss: 0.1620 - val_loss: 0.3767 - val_sparse_categorical_crossentropy: 0.1905 - val_sparse_categorical_accuracy: 0.9162 - val_scaled_adversarial_loss: 0.1862\n",
      "Epoch 150/1000\n",
      "9/9 [==============================] - 3s 389ms/step - loss: 0.3701 - sparse_categorical_crossentropy: 0.2156 - sparse_categorical_accuracy: 0.9096 - scaled_adversarial_loss: 0.1545 - val_loss: 0.4581 - val_sparse_categorical_crossentropy: 0.2255 - val_sparse_categorical_accuracy: 0.9258 - val_scaled_adversarial_loss: 0.2326\n",
      "Epoch 151/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.4013 - sparse_categorical_crossentropy: 0.2338 - sparse_categorical_accuracy: 0.9036 - scaled_adversarial_loss: 0.1675 - val_loss: 0.3617 - val_sparse_categorical_crossentropy: 0.1940 - val_sparse_categorical_accuracy: 0.9326 - val_scaled_adversarial_loss: 0.1677\n",
      "Epoch 152/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.3785 - sparse_categorical_crossentropy: 0.2127 - sparse_categorical_accuracy: 0.9142 - scaled_adversarial_loss: 0.1657 - val_loss: 0.3884 - val_sparse_categorical_crossentropy: 0.2022 - val_sparse_categorical_accuracy: 0.9229 - val_scaled_adversarial_loss: 0.1862\n",
      "Epoch 153/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.3610 - sparse_categorical_crossentropy: 0.2024 - sparse_categorical_accuracy: 0.9156 - scaled_adversarial_loss: 0.1585 - val_loss: 0.3789 - val_sparse_categorical_crossentropy: 0.1834 - val_sparse_categorical_accuracy: 0.9306 - val_scaled_adversarial_loss: 0.1955\n",
      "Epoch 154/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.3422 - sparse_categorical_crossentropy: 0.1920 - sparse_categorical_accuracy: 0.9202 - scaled_adversarial_loss: 0.1502 - val_loss: 0.3786 - val_sparse_categorical_crossentropy: 0.1687 - val_sparse_categorical_accuracy: 0.9258 - val_scaled_adversarial_loss: 0.2099\n",
      "Epoch 155/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.3642 - sparse_categorical_crossentropy: 0.1988 - sparse_categorical_accuracy: 0.9219 - scaled_adversarial_loss: 0.1653 - val_loss: 0.3709 - val_sparse_categorical_crossentropy: 0.1825 - val_sparse_categorical_accuracy: 0.9249 - val_scaled_adversarial_loss: 0.1884\n",
      "Epoch 156/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.3445 - sparse_categorical_crossentropy: 0.1937 - sparse_categorical_accuracy: 0.9188 - scaled_adversarial_loss: 0.1508 - val_loss: 0.3675 - val_sparse_categorical_crossentropy: 0.1518 - val_sparse_categorical_accuracy: 0.9345 - val_scaled_adversarial_loss: 0.2157\n",
      "Epoch 157/1000\n",
      "9/9 [==============================] - 3s 389ms/step - loss: 0.3490 - sparse_categorical_crossentropy: 0.1979 - sparse_categorical_accuracy: 0.9192 - scaled_adversarial_loss: 0.1511 - val_loss: 0.3763 - val_sparse_categorical_crossentropy: 0.1777 - val_sparse_categorical_accuracy: 0.9258 - val_scaled_adversarial_loss: 0.1986\n",
      "Epoch 158/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.3544 - sparse_categorical_crossentropy: 0.2015 - sparse_categorical_accuracy: 0.9161 - scaled_adversarial_loss: 0.1529 - val_loss: 0.3912 - val_sparse_categorical_crossentropy: 0.2080 - val_sparse_categorical_accuracy: 0.9287 - val_scaled_adversarial_loss: 0.1832\n",
      "Epoch 159/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.3524 - sparse_categorical_crossentropy: 0.1943 - sparse_categorical_accuracy: 0.9260 - scaled_adversarial_loss: 0.1580 - val_loss: 0.3675 - val_sparse_categorical_crossentropy: 0.1792 - val_sparse_categorical_accuracy: 0.9374 - val_scaled_adversarial_loss: 0.1882\n",
      "Epoch 160/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.3548 - sparse_categorical_crossentropy: 0.2007 - sparse_categorical_accuracy: 0.9262 - scaled_adversarial_loss: 0.1540 - val_loss: 0.3539 - val_sparse_categorical_crossentropy: 0.1673 - val_sparse_categorical_accuracy: 0.9316 - val_scaled_adversarial_loss: 0.1867\n",
      "Epoch 161/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.3551 - sparse_categorical_crossentropy: 0.1954 - sparse_categorical_accuracy: 0.9248 - scaled_adversarial_loss: 0.1597 - val_loss: 0.3349 - val_sparse_categorical_crossentropy: 0.1642 - val_sparse_categorical_accuracy: 0.9355 - val_scaled_adversarial_loss: 0.1707\n",
      "Epoch 162/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.3425 - sparse_categorical_crossentropy: 0.1934 - sparse_categorical_accuracy: 0.9233 - scaled_adversarial_loss: 0.1491 - val_loss: 0.3869 - val_sparse_categorical_crossentropy: 0.1723 - val_sparse_categorical_accuracy: 0.9355 - val_scaled_adversarial_loss: 0.2146\n",
      "Epoch 163/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.3330 - sparse_categorical_crossentropy: 0.1830 - sparse_categorical_accuracy: 0.9354 - scaled_adversarial_loss: 0.1500 - val_loss: 0.3309 - val_sparse_categorical_crossentropy: 0.1548 - val_sparse_categorical_accuracy: 0.9470 - val_scaled_adversarial_loss: 0.1761\n",
      "Epoch 164/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.3343 - sparse_categorical_crossentropy: 0.1829 - sparse_categorical_accuracy: 0.9279 - scaled_adversarial_loss: 0.1514 - val_loss: 0.3522 - val_sparse_categorical_crossentropy: 0.1880 - val_sparse_categorical_accuracy: 0.9432 - val_scaled_adversarial_loss: 0.1642\n",
      "Epoch 165/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.3447 - sparse_categorical_crossentropy: 0.1950 - sparse_categorical_accuracy: 0.9262 - scaled_adversarial_loss: 0.1497 - val_loss: 0.3480 - val_sparse_categorical_crossentropy: 0.2020 - val_sparse_categorical_accuracy: 0.9287 - val_scaled_adversarial_loss: 0.1461\n",
      "Epoch 166/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.3447 - sparse_categorical_crossentropy: 0.2017 - sparse_categorical_accuracy: 0.9154 - scaled_adversarial_loss: 0.1430 - val_loss: 0.3725 - val_sparse_categorical_crossentropy: 0.2106 - val_sparse_categorical_accuracy: 0.9200 - val_scaled_adversarial_loss: 0.1620\n",
      "Epoch 167/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.3306 - sparse_categorical_crossentropy: 0.1824 - sparse_categorical_accuracy: 0.9250 - scaled_adversarial_loss: 0.1482 - val_loss: 0.2940 - val_sparse_categorical_crossentropy: 0.1497 - val_sparse_categorical_accuracy: 0.9461 - val_scaled_adversarial_loss: 0.1444\n",
      "Epoch 168/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.3009 - sparse_categorical_crossentropy: 0.1588 - sparse_categorical_accuracy: 0.9378 - scaled_adversarial_loss: 0.1421 - val_loss: 0.3237 - val_sparse_categorical_crossentropy: 0.1651 - val_sparse_categorical_accuracy: 0.9489 - val_scaled_adversarial_loss: 0.1586\n",
      "Epoch 169/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.3228 - sparse_categorical_crossentropy: 0.1795 - sparse_categorical_accuracy: 0.9366 - scaled_adversarial_loss: 0.1433 - val_loss: 0.3332 - val_sparse_categorical_crossentropy: 0.1847 - val_sparse_categorical_accuracy: 0.9509 - val_scaled_adversarial_loss: 0.1485\n",
      "Epoch 170/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.3040 - sparse_categorical_crossentropy: 0.1645 - sparse_categorical_accuracy: 0.9441 - scaled_adversarial_loss: 0.1395 - val_loss: 0.2841 - val_sparse_categorical_crossentropy: 0.1595 - val_sparse_categorical_accuracy: 0.9489 - val_scaled_adversarial_loss: 0.1246\n",
      "Epoch 171/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.2961 - sparse_categorical_crossentropy: 0.1573 - sparse_categorical_accuracy: 0.9438 - scaled_adversarial_loss: 0.1388 - val_loss: 0.3034 - val_sparse_categorical_crossentropy: 0.1672 - val_sparse_categorical_accuracy: 0.9499 - val_scaled_adversarial_loss: 0.1362\n",
      "Epoch 172/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.3246 - sparse_categorical_crossentropy: 0.1846 - sparse_categorical_accuracy: 0.9388 - scaled_adversarial_loss: 0.1400 - val_loss: 0.2943 - val_sparse_categorical_crossentropy: 0.1474 - val_sparse_categorical_accuracy: 0.9480 - val_scaled_adversarial_loss: 0.1469\n",
      "Epoch 173/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.2968 - sparse_categorical_crossentropy: 0.1666 - sparse_categorical_accuracy: 0.9337 - scaled_adversarial_loss: 0.1302 - val_loss: 0.3861 - val_sparse_categorical_crossentropy: 0.1943 - val_sparse_categorical_accuracy: 0.9538 - val_scaled_adversarial_loss: 0.1918\n",
      "Epoch 174/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.3078 - sparse_categorical_crossentropy: 0.1638 - sparse_categorical_accuracy: 0.9392 - scaled_adversarial_loss: 0.1440 - val_loss: 0.2799 - val_sparse_categorical_crossentropy: 0.1387 - val_sparse_categorical_accuracy: 0.9518 - val_scaled_adversarial_loss: 0.1411\n",
      "Epoch 175/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.2887 - sparse_categorical_crossentropy: 0.1538 - sparse_categorical_accuracy: 0.9453 - scaled_adversarial_loss: 0.1349 - val_loss: 0.3468 - val_sparse_categorical_crossentropy: 0.1673 - val_sparse_categorical_accuracy: 0.9557 - val_scaled_adversarial_loss: 0.1796\n",
      "Epoch 176/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.2970 - sparse_categorical_crossentropy: 0.1591 - sparse_categorical_accuracy: 0.9441 - scaled_adversarial_loss: 0.1380 - val_loss: 0.3063 - val_sparse_categorical_crossentropy: 0.1643 - val_sparse_categorical_accuracy: 0.9566 - val_scaled_adversarial_loss: 0.1419\n",
      "Epoch 177/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.2977 - sparse_categorical_crossentropy: 0.1560 - sparse_categorical_accuracy: 0.9448 - scaled_adversarial_loss: 0.1418 - val_loss: 0.3106 - val_sparse_categorical_crossentropy: 0.1753 - val_sparse_categorical_accuracy: 0.9499 - val_scaled_adversarial_loss: 0.1353\n",
      "Epoch 178/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.2676 - sparse_categorical_crossentropy: 0.1372 - sparse_categorical_accuracy: 0.9501 - scaled_adversarial_loss: 0.1304 - val_loss: 0.2847 - val_sparse_categorical_crossentropy: 0.1523 - val_sparse_categorical_accuracy: 0.9586 - val_scaled_adversarial_loss: 0.1324\n",
      "Epoch 179/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.2694 - sparse_categorical_crossentropy: 0.1440 - sparse_categorical_accuracy: 0.9443 - scaled_adversarial_loss: 0.1254 - val_loss: 0.3766 - val_sparse_categorical_crossentropy: 0.2244 - val_sparse_categorical_accuracy: 0.9557 - val_scaled_adversarial_loss: 0.1523\n",
      "Epoch 180/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.2876 - sparse_categorical_crossentropy: 0.1549 - sparse_categorical_accuracy: 0.9433 - scaled_adversarial_loss: 0.1328 - val_loss: 0.3652 - val_sparse_categorical_crossentropy: 0.2328 - val_sparse_categorical_accuracy: 0.9451 - val_scaled_adversarial_loss: 0.1324\n",
      "Epoch 181/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.3140 - sparse_categorical_crossentropy: 0.1743 - sparse_categorical_accuracy: 0.9330 - scaled_adversarial_loss: 0.1397 - val_loss: 0.3293 - val_sparse_categorical_crossentropy: 0.1802 - val_sparse_categorical_accuracy: 0.9470 - val_scaled_adversarial_loss: 0.1491\n",
      "Epoch 182/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.3003 - sparse_categorical_crossentropy: 0.1673 - sparse_categorical_accuracy: 0.9376 - scaled_adversarial_loss: 0.1330 - val_loss: 0.3059 - val_sparse_categorical_crossentropy: 0.1650 - val_sparse_categorical_accuracy: 0.9538 - val_scaled_adversarial_loss: 0.1409\n",
      "Epoch 183/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.2851 - sparse_categorical_crossentropy: 0.1448 - sparse_categorical_accuracy: 0.9503 - scaled_adversarial_loss: 0.1403 - val_loss: 0.3644 - val_sparse_categorical_crossentropy: 0.2194 - val_sparse_categorical_accuracy: 0.9547 - val_scaled_adversarial_loss: 0.1450\n",
      "Epoch 184/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.3031 - sparse_categorical_crossentropy: 0.1699 - sparse_categorical_accuracy: 0.9477 - scaled_adversarial_loss: 0.1332 - val_loss: 0.3063 - val_sparse_categorical_crossentropy: 0.1953 - val_sparse_categorical_accuracy: 0.9576 - val_scaled_adversarial_loss: 0.1110\n",
      "Epoch 185/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.2887 - sparse_categorical_crossentropy: 0.1578 - sparse_categorical_accuracy: 0.9479 - scaled_adversarial_loss: 0.1309 - val_loss: 0.2691 - val_sparse_categorical_crossentropy: 0.1567 - val_sparse_categorical_accuracy: 0.9586 - val_scaled_adversarial_loss: 0.1124\n",
      "Epoch 186/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.2933 - sparse_categorical_crossentropy: 0.1615 - sparse_categorical_accuracy: 0.9424 - scaled_adversarial_loss: 0.1318 - val_loss: 0.2774 - val_sparse_categorical_crossentropy: 0.1722 - val_sparse_categorical_accuracy: 0.9499 - val_scaled_adversarial_loss: 0.1052\n",
      "Epoch 187/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.2880 - sparse_categorical_crossentropy: 0.1499 - sparse_categorical_accuracy: 0.9474 - scaled_adversarial_loss: 0.1381 - val_loss: 0.2731 - val_sparse_categorical_crossentropy: 0.1503 - val_sparse_categorical_accuracy: 0.9615 - val_scaled_adversarial_loss: 0.1228\n",
      "Epoch 188/1000\n",
      "9/9 [==============================] - 4s 393ms/step - loss: 0.2663 - sparse_categorical_crossentropy: 0.1372 - sparse_categorical_accuracy: 0.9537 - scaled_adversarial_loss: 0.1291 - val_loss: 0.3007 - val_sparse_categorical_crossentropy: 0.1865 - val_sparse_categorical_accuracy: 0.9595 - val_scaled_adversarial_loss: 0.1142\n",
      "Epoch 189/1000\n",
      "9/9 [==============================] - 4s 399ms/step - loss: 0.2520 - sparse_categorical_crossentropy: 0.1292 - sparse_categorical_accuracy: 0.9547 - scaled_adversarial_loss: 0.1227 - val_loss: 0.3553 - val_sparse_categorical_crossentropy: 0.2145 - val_sparse_categorical_accuracy: 0.9538 - val_scaled_adversarial_loss: 0.1409\n",
      "Epoch 190/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.2693 - sparse_categorical_crossentropy: 0.1521 - sparse_categorical_accuracy: 0.9518 - scaled_adversarial_loss: 0.1172 - val_loss: 0.2664 - val_sparse_categorical_crossentropy: 0.1599 - val_sparse_categorical_accuracy: 0.9605 - val_scaled_adversarial_loss: 0.1064\n",
      "Epoch 191/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.2398 - sparse_categorical_crossentropy: 0.1298 - sparse_categorical_accuracy: 0.9499 - scaled_adversarial_loss: 0.1100 - val_loss: 0.2378 - val_sparse_categorical_crossentropy: 0.1118 - val_sparse_categorical_accuracy: 0.9528 - val_scaled_adversarial_loss: 0.1260\n",
      "Epoch 192/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.2714 - sparse_categorical_crossentropy: 0.1466 - sparse_categorical_accuracy: 0.9458 - scaled_adversarial_loss: 0.1248 - val_loss: 0.2611 - val_sparse_categorical_crossentropy: 0.1222 - val_sparse_categorical_accuracy: 0.9489 - val_scaled_adversarial_loss: 0.1390\n",
      "Epoch 193/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.2703 - sparse_categorical_crossentropy: 0.1476 - sparse_categorical_accuracy: 0.9421 - scaled_adversarial_loss: 0.1227 - val_loss: 0.2406 - val_sparse_categorical_crossentropy: 0.1199 - val_sparse_categorical_accuracy: 0.9432 - val_scaled_adversarial_loss: 0.1207\n",
      "Epoch 194/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.2725 - sparse_categorical_crossentropy: 0.1472 - sparse_categorical_accuracy: 0.9438 - scaled_adversarial_loss: 0.1253 - val_loss: 0.2667 - val_sparse_categorical_crossentropy: 0.1245 - val_sparse_categorical_accuracy: 0.9595 - val_scaled_adversarial_loss: 0.1422\n",
      "Epoch 195/1000\n",
      "9/9 [==============================] - 3s 376ms/step - loss: 0.2611 - sparse_categorical_crossentropy: 0.1277 - sparse_categorical_accuracy: 0.9532 - scaled_adversarial_loss: 0.1334 - val_loss: 0.2755 - val_sparse_categorical_crossentropy: 0.1595 - val_sparse_categorical_accuracy: 0.9605 - val_scaled_adversarial_loss: 0.1160\n",
      "Epoch 196/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.2372 - sparse_categorical_crossentropy: 0.1259 - sparse_categorical_accuracy: 0.9506 - scaled_adversarial_loss: 0.1113 - val_loss: 0.2420 - val_sparse_categorical_crossentropy: 0.1363 - val_sparse_categorical_accuracy: 0.9605 - val_scaled_adversarial_loss: 0.1056\n",
      "Epoch 197/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.2511 - sparse_categorical_crossentropy: 0.1342 - sparse_categorical_accuracy: 0.9532 - scaled_adversarial_loss: 0.1168 - val_loss: 0.2440 - val_sparse_categorical_crossentropy: 0.1432 - val_sparse_categorical_accuracy: 0.9615 - val_scaled_adversarial_loss: 0.1008\n",
      "Epoch 198/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.2319 - sparse_categorical_crossentropy: 0.1157 - sparse_categorical_accuracy: 0.9573 - scaled_adversarial_loss: 0.1162 - val_loss: 0.2536 - val_sparse_categorical_crossentropy: 0.1625 - val_sparse_categorical_accuracy: 0.9586 - val_scaled_adversarial_loss: 0.0912\n",
      "Epoch 199/1000\n",
      "9/9 [==============================] - 3s 389ms/step - loss: 0.2241 - sparse_categorical_crossentropy: 0.1097 - sparse_categorical_accuracy: 0.9619 - scaled_adversarial_loss: 0.1144 - val_loss: 0.3136 - val_sparse_categorical_crossentropy: 0.1574 - val_sparse_categorical_accuracy: 0.9586 - val_scaled_adversarial_loss: 0.1562\n",
      "Epoch 200/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.2373 - sparse_categorical_crossentropy: 0.1232 - sparse_categorical_accuracy: 0.9583 - scaled_adversarial_loss: 0.1141 - val_loss: 0.2928 - val_sparse_categorical_crossentropy: 0.1657 - val_sparse_categorical_accuracy: 0.9586 - val_scaled_adversarial_loss: 0.1271\n",
      "Epoch 201/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.2401 - sparse_categorical_crossentropy: 0.1249 - sparse_categorical_accuracy: 0.9573 - scaled_adversarial_loss: 0.1152 - val_loss: 0.2884 - val_sparse_categorical_crossentropy: 0.1796 - val_sparse_categorical_accuracy: 0.9586 - val_scaled_adversarial_loss: 0.1089\n",
      "Epoch 202/1000\n",
      "9/9 [==============================] - 3s 375ms/step - loss: 0.2244 - sparse_categorical_crossentropy: 0.1108 - sparse_categorical_accuracy: 0.9590 - scaled_adversarial_loss: 0.1136 - val_loss: 0.2464 - val_sparse_categorical_crossentropy: 0.1228 - val_sparse_categorical_accuracy: 0.9615 - val_scaled_adversarial_loss: 0.1236\n",
      "Epoch 203/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.2234 - sparse_categorical_crossentropy: 0.1105 - sparse_categorical_accuracy: 0.9590 - scaled_adversarial_loss: 0.1129 - val_loss: 0.2322 - val_sparse_categorical_crossentropy: 0.1243 - val_sparse_categorical_accuracy: 0.9595 - val_scaled_adversarial_loss: 0.1079\n",
      "Epoch 204/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.2407 - sparse_categorical_crossentropy: 0.1250 - sparse_categorical_accuracy: 0.9583 - scaled_adversarial_loss: 0.1157 - val_loss: 0.2247 - val_sparse_categorical_crossentropy: 0.1328 - val_sparse_categorical_accuracy: 0.9634 - val_scaled_adversarial_loss: 0.0919\n",
      "Epoch 205/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.2190 - sparse_categorical_crossentropy: 0.1132 - sparse_categorical_accuracy: 0.9619 - scaled_adversarial_loss: 0.1058 - val_loss: 0.2341 - val_sparse_categorical_crossentropy: 0.1280 - val_sparse_categorical_accuracy: 0.9672 - val_scaled_adversarial_loss: 0.1060\n",
      "Epoch 206/1000\n",
      "9/9 [==============================] - 3s 392ms/step - loss: 0.2242 - sparse_categorical_crossentropy: 0.1176 - sparse_categorical_accuracy: 0.9547 - scaled_adversarial_loss: 0.1065 - val_loss: 0.2334 - val_sparse_categorical_crossentropy: 0.1206 - val_sparse_categorical_accuracy: 0.9653 - val_scaled_adversarial_loss: 0.1127\n",
      "Epoch 207/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.2155 - sparse_categorical_crossentropy: 0.1041 - sparse_categorical_accuracy: 0.9631 - scaled_adversarial_loss: 0.1114 - val_loss: 0.1961 - val_sparse_categorical_crossentropy: 0.1021 - val_sparse_categorical_accuracy: 0.9672 - val_scaled_adversarial_loss: 0.0940\n",
      "Epoch 208/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.2114 - sparse_categorical_crossentropy: 0.1020 - sparse_categorical_accuracy: 0.9626 - scaled_adversarial_loss: 0.1094 - val_loss: 0.2113 - val_sparse_categorical_crossentropy: 0.1194 - val_sparse_categorical_accuracy: 0.9672 - val_scaled_adversarial_loss: 0.0919\n",
      "Epoch 209/1000\n",
      "9/9 [==============================] - 4s 423ms/step - loss: 0.2110 - sparse_categorical_crossentropy: 0.1073 - sparse_categorical_accuracy: 0.9595 - scaled_adversarial_loss: 0.1037 - val_loss: 0.2172 - val_sparse_categorical_crossentropy: 0.1291 - val_sparse_categorical_accuracy: 0.9672 - val_scaled_adversarial_loss: 0.0881\n",
      "Epoch 210/1000\n",
      "9/9 [==============================] - 3s 375ms/step - loss: 0.2057 - sparse_categorical_crossentropy: 0.1027 - sparse_categorical_accuracy: 0.9634 - scaled_adversarial_loss: 0.1029 - val_loss: 0.2191 - val_sparse_categorical_crossentropy: 0.1196 - val_sparse_categorical_accuracy: 0.9682 - val_scaled_adversarial_loss: 0.0996\n",
      "Epoch 211/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.2097 - sparse_categorical_crossentropy: 0.1020 - sparse_categorical_accuracy: 0.9658 - scaled_adversarial_loss: 0.1076 - val_loss: 0.2426 - val_sparse_categorical_crossentropy: 0.1352 - val_sparse_categorical_accuracy: 0.9634 - val_scaled_adversarial_loss: 0.1074\n",
      "Epoch 212/1000\n",
      "9/9 [==============================] - 3s 386ms/step - loss: 0.2220 - sparse_categorical_crossentropy: 0.1089 - sparse_categorical_accuracy: 0.9571 - scaled_adversarial_loss: 0.1130 - val_loss: 0.2571 - val_sparse_categorical_crossentropy: 0.1431 - val_sparse_categorical_accuracy: 0.9547 - val_scaled_adversarial_loss: 0.1140\n",
      "Epoch 213/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.2253 - sparse_categorical_crossentropy: 0.1209 - sparse_categorical_accuracy: 0.9540 - scaled_adversarial_loss: 0.1044 - val_loss: 0.2778 - val_sparse_categorical_crossentropy: 0.1735 - val_sparse_categorical_accuracy: 0.9499 - val_scaled_adversarial_loss: 0.1042\n",
      "Epoch 214/1000\n",
      "9/9 [==============================] - 4s 400ms/step - loss: 0.2220 - sparse_categorical_crossentropy: 0.1130 - sparse_categorical_accuracy: 0.9568 - scaled_adversarial_loss: 0.1090 - val_loss: 0.2198 - val_sparse_categorical_crossentropy: 0.1180 - val_sparse_categorical_accuracy: 0.9692 - val_scaled_adversarial_loss: 0.1018\n",
      "Epoch 215/1000\n",
      "9/9 [==============================] - 3s 383ms/step - loss: 0.2078 - sparse_categorical_crossentropy: 0.0997 - sparse_categorical_accuracy: 0.9636 - scaled_adversarial_loss: 0.1081 - val_loss: 0.2049 - val_sparse_categorical_crossentropy: 0.1189 - val_sparse_categorical_accuracy: 0.9663 - val_scaled_adversarial_loss: 0.0860\n",
      "Epoch 216/1000\n",
      "9/9 [==============================] - 4s 397ms/step - loss: 0.1927 - sparse_categorical_crossentropy: 0.0913 - sparse_categorical_accuracy: 0.9629 - scaled_adversarial_loss: 0.1014 - val_loss: 0.2315 - val_sparse_categorical_crossentropy: 0.1254 - val_sparse_categorical_accuracy: 0.9663 - val_scaled_adversarial_loss: 0.1061\n",
      "Epoch 217/1000\n",
      "9/9 [==============================] - 4s 410ms/step - loss: 0.2063 - sparse_categorical_crossentropy: 0.0960 - sparse_categorical_accuracy: 0.9665 - scaled_adversarial_loss: 0.1103 - val_loss: 0.2017 - val_sparse_categorical_crossentropy: 0.1079 - val_sparse_categorical_accuracy: 0.9730 - val_scaled_adversarial_loss: 0.0938\n",
      "Epoch 218/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1958 - sparse_categorical_crossentropy: 0.0939 - sparse_categorical_accuracy: 0.9677 - scaled_adversarial_loss: 0.1019 - val_loss: 0.1994 - val_sparse_categorical_crossentropy: 0.1047 - val_sparse_categorical_accuracy: 0.9711 - val_scaled_adversarial_loss: 0.0947\n",
      "Epoch 219/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.2257 - sparse_categorical_crossentropy: 0.1229 - sparse_categorical_accuracy: 0.9595 - scaled_adversarial_loss: 0.1027 - val_loss: 0.2716 - val_sparse_categorical_crossentropy: 0.1678 - val_sparse_categorical_accuracy: 0.9663 - val_scaled_adversarial_loss: 0.1038\n",
      "Epoch 220/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.2054 - sparse_categorical_crossentropy: 0.1073 - sparse_categorical_accuracy: 0.9605 - scaled_adversarial_loss: 0.0982 - val_loss: 0.2101 - val_sparse_categorical_crossentropy: 0.1120 - val_sparse_categorical_accuracy: 0.9672 - val_scaled_adversarial_loss: 0.0981\n",
      "Epoch 221/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1987 - sparse_categorical_crossentropy: 0.0937 - sparse_categorical_accuracy: 0.9646 - scaled_adversarial_loss: 0.1050 - val_loss: 0.1750 - val_sparse_categorical_crossentropy: 0.0882 - val_sparse_categorical_accuracy: 0.9644 - val_scaled_adversarial_loss: 0.0868\n",
      "Epoch 222/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.2033 - sparse_categorical_crossentropy: 0.0962 - sparse_categorical_accuracy: 0.9667 - scaled_adversarial_loss: 0.1071 - val_loss: 0.1657 - val_sparse_categorical_crossentropy: 0.0721 - val_sparse_categorical_accuracy: 0.9721 - val_scaled_adversarial_loss: 0.0935\n",
      "Epoch 223/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.2050 - sparse_categorical_crossentropy: 0.1021 - sparse_categorical_accuracy: 0.9609 - scaled_adversarial_loss: 0.1029 - val_loss: 0.2012 - val_sparse_categorical_crossentropy: 0.1044 - val_sparse_categorical_accuracy: 0.9701 - val_scaled_adversarial_loss: 0.0968\n",
      "Epoch 224/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.2070 - sparse_categorical_crossentropy: 0.0992 - sparse_categorical_accuracy: 0.9631 - scaled_adversarial_loss: 0.1078 - val_loss: 0.2149 - val_sparse_categorical_crossentropy: 0.1136 - val_sparse_categorical_accuracy: 0.9730 - val_scaled_adversarial_loss: 0.1013\n",
      "Epoch 225/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1928 - sparse_categorical_crossentropy: 0.0891 - sparse_categorical_accuracy: 0.9662 - scaled_adversarial_loss: 0.1037 - val_loss: 0.1940 - val_sparse_categorical_crossentropy: 0.0948 - val_sparse_categorical_accuracy: 0.9721 - val_scaled_adversarial_loss: 0.0993\n",
      "Epoch 226/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1929 - sparse_categorical_crossentropy: 0.0906 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.1023 - val_loss: 0.1886 - val_sparse_categorical_crossentropy: 0.0808 - val_sparse_categorical_accuracy: 0.9701 - val_scaled_adversarial_loss: 0.1078\n",
      "Epoch 227/1000\n",
      "9/9 [==============================] - 3s 384ms/step - loss: 0.2170 - sparse_categorical_crossentropy: 0.1064 - sparse_categorical_accuracy: 0.9593 - scaled_adversarial_loss: 0.1106 - val_loss: 0.1838 - val_sparse_categorical_crossentropy: 0.0823 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.1015\n",
      "Epoch 228/1000\n",
      "9/9 [==============================] - 3s 375ms/step - loss: 0.2106 - sparse_categorical_crossentropy: 0.0955 - sparse_categorical_accuracy: 0.9629 - scaled_adversarial_loss: 0.1150 - val_loss: 0.2145 - val_sparse_categorical_crossentropy: 0.1159 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0986\n",
      "Epoch 229/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.2004 - sparse_categorical_crossentropy: 0.0869 - sparse_categorical_accuracy: 0.9653 - scaled_adversarial_loss: 0.1135 - val_loss: 0.1932 - val_sparse_categorical_crossentropy: 0.0991 - val_sparse_categorical_accuracy: 0.9701 - val_scaled_adversarial_loss: 0.0941\n",
      "Epoch 230/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.1935 - sparse_categorical_crossentropy: 0.0885 - sparse_categorical_accuracy: 0.9672 - scaled_adversarial_loss: 0.1050 - val_loss: 0.2023 - val_sparse_categorical_crossentropy: 0.1054 - val_sparse_categorical_accuracy: 0.9692 - val_scaled_adversarial_loss: 0.0969\n",
      "Epoch 231/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1809 - sparse_categorical_crossentropy: 0.0813 - sparse_categorical_accuracy: 0.9675 - scaled_adversarial_loss: 0.0995 - val_loss: 0.2081 - val_sparse_categorical_crossentropy: 0.1084 - val_sparse_categorical_accuracy: 0.9711 - val_scaled_adversarial_loss: 0.0997\n",
      "Epoch 232/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1966 - sparse_categorical_crossentropy: 0.0916 - sparse_categorical_accuracy: 0.9660 - scaled_adversarial_loss: 0.1051 - val_loss: 0.2071 - val_sparse_categorical_crossentropy: 0.0968 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.1103\n",
      "Epoch 233/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1970 - sparse_categorical_crossentropy: 0.0965 - sparse_categorical_accuracy: 0.9648 - scaled_adversarial_loss: 0.1004 - val_loss: 0.1852 - val_sparse_categorical_crossentropy: 0.0964 - val_sparse_categorical_accuracy: 0.9701 - val_scaled_adversarial_loss: 0.0887\n",
      "Epoch 234/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1833 - sparse_categorical_crossentropy: 0.0838 - sparse_categorical_accuracy: 0.9679 - scaled_adversarial_loss: 0.0995 - val_loss: 0.1809 - val_sparse_categorical_crossentropy: 0.0989 - val_sparse_categorical_accuracy: 0.9701 - val_scaled_adversarial_loss: 0.0820\n",
      "Epoch 235/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1867 - sparse_categorical_crossentropy: 0.0891 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.0977 - val_loss: 0.1698 - val_sparse_categorical_crossentropy: 0.0816 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0883\n",
      "Epoch 236/1000\n",
      "9/9 [==============================] - 4s 391ms/step - loss: 0.1846 - sparse_categorical_crossentropy: 0.0870 - sparse_categorical_accuracy: 0.9713 - scaled_adversarial_loss: 0.0977 - val_loss: 0.1918 - val_sparse_categorical_crossentropy: 0.1074 - val_sparse_categorical_accuracy: 0.9701 - val_scaled_adversarial_loss: 0.0844\n",
      "Epoch 237/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.2235 - sparse_categorical_crossentropy: 0.1205 - sparse_categorical_accuracy: 0.9581 - scaled_adversarial_loss: 0.1030 - val_loss: 0.1763 - val_sparse_categorical_crossentropy: 0.0959 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0804\n",
      "Epoch 238/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.2119 - sparse_categorical_crossentropy: 0.1064 - sparse_categorical_accuracy: 0.9585 - scaled_adversarial_loss: 0.1056 - val_loss: 0.1783 - val_sparse_categorical_crossentropy: 0.0959 - val_sparse_categorical_accuracy: 0.9711 - val_scaled_adversarial_loss: 0.0825\n",
      "Epoch 239/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.2071 - sparse_categorical_crossentropy: 0.1025 - sparse_categorical_accuracy: 0.9643 - scaled_adversarial_loss: 0.1046 - val_loss: 0.1737 - val_sparse_categorical_crossentropy: 0.0794 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0943\n",
      "Epoch 240/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.2006 - sparse_categorical_crossentropy: 0.0936 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.1070 - val_loss: 0.1777 - val_sparse_categorical_crossentropy: 0.0863 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0913\n",
      "Epoch 241/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.2008 - sparse_categorical_crossentropy: 0.0913 - sparse_categorical_accuracy: 0.9665 - scaled_adversarial_loss: 0.1095 - val_loss: 0.1763 - val_sparse_categorical_crossentropy: 0.0952 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.0812\n",
      "Epoch 242/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.2077 - sparse_categorical_crossentropy: 0.1034 - sparse_categorical_accuracy: 0.9696 - scaled_adversarial_loss: 0.1043 - val_loss: 0.1873 - val_sparse_categorical_crossentropy: 0.0855 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.1018\n",
      "Epoch 243/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.2057 - sparse_categorical_crossentropy: 0.0962 - sparse_categorical_accuracy: 0.9701 - scaled_adversarial_loss: 0.1096 - val_loss: 0.2182 - val_sparse_categorical_crossentropy: 0.1169 - val_sparse_categorical_accuracy: 0.9730 - val_scaled_adversarial_loss: 0.1012\n",
      "Epoch 244/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1897 - sparse_categorical_crossentropy: 0.0898 - sparse_categorical_accuracy: 0.9687 - scaled_adversarial_loss: 0.0999 - val_loss: 0.1624 - val_sparse_categorical_crossentropy: 0.0772 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0851\n",
      "Epoch 245/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1860 - sparse_categorical_crossentropy: 0.0850 - sparse_categorical_accuracy: 0.9687 - scaled_adversarial_loss: 0.1010 - val_loss: 0.2065 - val_sparse_categorical_crossentropy: 0.1030 - val_sparse_categorical_accuracy: 0.9711 - val_scaled_adversarial_loss: 0.1034\n",
      "Epoch 246/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.1957 - sparse_categorical_crossentropy: 0.0869 - sparse_categorical_accuracy: 0.9679 - scaled_adversarial_loss: 0.1088 - val_loss: 0.1868 - val_sparse_categorical_crossentropy: 0.1099 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0769\n",
      "Epoch 247/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.1916 - sparse_categorical_crossentropy: 0.0898 - sparse_categorical_accuracy: 0.9677 - scaled_adversarial_loss: 0.1018 - val_loss: 0.2049 - val_sparse_categorical_crossentropy: 0.0969 - val_sparse_categorical_accuracy: 0.9711 - val_scaled_adversarial_loss: 0.1080\n",
      "Epoch 248/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1865 - sparse_categorical_crossentropy: 0.0850 - sparse_categorical_accuracy: 0.9696 - scaled_adversarial_loss: 0.1016 - val_loss: 0.2430 - val_sparse_categorical_crossentropy: 0.1504 - val_sparse_categorical_accuracy: 0.9682 - val_scaled_adversarial_loss: 0.0926\n",
      "Epoch 249/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1835 - sparse_categorical_crossentropy: 0.0852 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.0983 - val_loss: 0.2469 - val_sparse_categorical_crossentropy: 0.1379 - val_sparse_categorical_accuracy: 0.9730 - val_scaled_adversarial_loss: 0.1089\n",
      "Epoch 250/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.2002 - sparse_categorical_crossentropy: 0.0954 - sparse_categorical_accuracy: 0.9679 - scaled_adversarial_loss: 0.1049 - val_loss: 0.1836 - val_sparse_categorical_crossentropy: 0.0698 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.1138\n",
      "Epoch 251/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1881 - sparse_categorical_crossentropy: 0.0872 - sparse_categorical_accuracy: 0.9658 - scaled_adversarial_loss: 0.1009 - val_loss: 0.2227 - val_sparse_categorical_crossentropy: 0.0993 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.1234\n",
      "Epoch 252/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1819 - sparse_categorical_crossentropy: 0.0826 - sparse_categorical_accuracy: 0.9696 - scaled_adversarial_loss: 0.0993 - val_loss: 0.1581 - val_sparse_categorical_crossentropy: 0.0671 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0910\n",
      "Epoch 253/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1844 - sparse_categorical_crossentropy: 0.0829 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.1015 - val_loss: 0.2197 - val_sparse_categorical_crossentropy: 0.1156 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.1041\n",
      "Epoch 254/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1739 - sparse_categorical_crossentropy: 0.0744 - sparse_categorical_accuracy: 0.9703 - scaled_adversarial_loss: 0.0995 - val_loss: 0.1771 - val_sparse_categorical_crossentropy: 0.0945 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0826\n",
      "Epoch 255/1000\n",
      "9/9 [==============================] - 3s 390ms/step - loss: 0.1755 - sparse_categorical_crossentropy: 0.0837 - sparse_categorical_accuracy: 0.9689 - scaled_adversarial_loss: 0.0917 - val_loss: 0.1946 - val_sparse_categorical_crossentropy: 0.1001 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0944\n",
      "Epoch 256/1000\n",
      "9/9 [==============================] - 4s 409ms/step - loss: 0.1904 - sparse_categorical_crossentropy: 0.0883 - sparse_categorical_accuracy: 0.9643 - scaled_adversarial_loss: 0.1021 - val_loss: 0.2387 - val_sparse_categorical_crossentropy: 0.1422 - val_sparse_categorical_accuracy: 0.9682 - val_scaled_adversarial_loss: 0.0965\n",
      "Epoch 257/1000\n",
      "9/9 [==============================] - 4s 422ms/step - loss: 0.1926 - sparse_categorical_crossentropy: 0.0919 - sparse_categorical_accuracy: 0.9643 - scaled_adversarial_loss: 0.1007 - val_loss: 0.2526 - val_sparse_categorical_crossentropy: 0.1222 - val_sparse_categorical_accuracy: 0.9672 - val_scaled_adversarial_loss: 0.1304\n",
      "Epoch 258/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1874 - sparse_categorical_crossentropy: 0.0883 - sparse_categorical_accuracy: 0.9655 - scaled_adversarial_loss: 0.0991 - val_loss: 0.1905 - val_sparse_categorical_crossentropy: 0.0844 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.1061\n",
      "Epoch 259/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1929 - sparse_categorical_crossentropy: 0.0844 - sparse_categorical_accuracy: 0.9696 - scaled_adversarial_loss: 0.1086 - val_loss: 0.1613 - val_sparse_categorical_crossentropy: 0.0752 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0861\n",
      "Epoch 260/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1747 - sparse_categorical_crossentropy: 0.0789 - sparse_categorical_accuracy: 0.9701 - scaled_adversarial_loss: 0.0959 - val_loss: 0.1911 - val_sparse_categorical_crossentropy: 0.1011 - val_sparse_categorical_accuracy: 0.9730 - val_scaled_adversarial_loss: 0.0900\n",
      "Epoch 261/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1795 - sparse_categorical_crossentropy: 0.0826 - sparse_categorical_accuracy: 0.9682 - scaled_adversarial_loss: 0.0969 - val_loss: 0.1474 - val_sparse_categorical_crossentropy: 0.0662 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0812\n",
      "Epoch 262/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1763 - sparse_categorical_crossentropy: 0.0782 - sparse_categorical_accuracy: 0.9713 - scaled_adversarial_loss: 0.0982 - val_loss: 0.1496 - val_sparse_categorical_crossentropy: 0.0690 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0807\n",
      "Epoch 263/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1905 - sparse_categorical_crossentropy: 0.0928 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0978 - val_loss: 0.1560 - val_sparse_categorical_crossentropy: 0.0673 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0887\n",
      "Epoch 264/1000\n",
      "9/9 [==============================] - 4s 434ms/step - loss: 0.2005 - sparse_categorical_crossentropy: 0.0916 - sparse_categorical_accuracy: 0.9699 - scaled_adversarial_loss: 0.1089 - val_loss: 0.1663 - val_sparse_categorical_crossentropy: 0.0734 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0929\n",
      "Epoch 265/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.2116 - sparse_categorical_crossentropy: 0.1066 - sparse_categorical_accuracy: 0.9636 - scaled_adversarial_loss: 0.1050 - val_loss: 0.2644 - val_sparse_categorical_crossentropy: 0.1217 - val_sparse_categorical_accuracy: 0.9644 - val_scaled_adversarial_loss: 0.1428\n",
      "Epoch 266/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.2278 - sparse_categorical_crossentropy: 0.1103 - sparse_categorical_accuracy: 0.9607 - scaled_adversarial_loss: 0.1176 - val_loss: 0.2775 - val_sparse_categorical_crossentropy: 0.0994 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.1780\n",
      "Epoch 267/1000\n",
      "9/9 [==============================] - 3s 392ms/step - loss: 0.1934 - sparse_categorical_crossentropy: 0.0848 - sparse_categorical_accuracy: 0.9713 - scaled_adversarial_loss: 0.1086 - val_loss: 0.2141 - val_sparse_categorical_crossentropy: 0.0946 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.1195\n",
      "Epoch 268/1000\n",
      "9/9 [==============================] - 4s 398ms/step - loss: 0.1928 - sparse_categorical_crossentropy: 0.0868 - sparse_categorical_accuracy: 0.9703 - scaled_adversarial_loss: 0.1060 - val_loss: 0.1490 - val_sparse_categorical_crossentropy: 0.0616 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0874\n",
      "Epoch 269/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1808 - sparse_categorical_crossentropy: 0.0775 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.1032 - val_loss: 0.1824 - val_sparse_categorical_crossentropy: 0.0912 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0912\n",
      "Epoch 270/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1708 - sparse_categorical_crossentropy: 0.0717 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0992 - val_loss: 0.1632 - val_sparse_categorical_crossentropy: 0.0715 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0917\n",
      "Epoch 271/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1708 - sparse_categorical_crossentropy: 0.0700 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.1008 - val_loss: 0.1600 - val_sparse_categorical_crossentropy: 0.0719 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0881\n",
      "Epoch 272/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.1742 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9723 - scaled_adversarial_loss: 0.1018 - val_loss: 0.1558 - val_sparse_categorical_crossentropy: 0.0630 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0927\n",
      "Epoch 273/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1821 - sparse_categorical_crossentropy: 0.0821 - sparse_categorical_accuracy: 0.9730 - scaled_adversarial_loss: 0.1000 - val_loss: 0.1842 - val_sparse_categorical_crossentropy: 0.0891 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0951\n",
      "Epoch 274/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1775 - sparse_categorical_crossentropy: 0.0797 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0978 - val_loss: 0.1767 - val_sparse_categorical_crossentropy: 0.0771 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0996\n",
      "Epoch 275/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1886 - sparse_categorical_crossentropy: 0.0821 - sparse_categorical_accuracy: 0.9737 - scaled_adversarial_loss: 0.1065 - val_loss: 0.1693 - val_sparse_categorical_crossentropy: 0.0819 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0874\n",
      "Epoch 276/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1804 - sparse_categorical_crossentropy: 0.0823 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0982 - val_loss: 0.1756 - val_sparse_categorical_crossentropy: 0.0716 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.1040\n",
      "Epoch 277/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1703 - sparse_categorical_crossentropy: 0.0663 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.1040 - val_loss: 0.1690 - val_sparse_categorical_crossentropy: 0.0629 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.1062\n",
      "Epoch 278/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1685 - sparse_categorical_crossentropy: 0.0716 - sparse_categorical_accuracy: 0.9720 - scaled_adversarial_loss: 0.0969 - val_loss: 0.1522 - val_sparse_categorical_crossentropy: 0.0646 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0876\n",
      "Epoch 279/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1598 - sparse_categorical_crossentropy: 0.0676 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0922 - val_loss: 0.1802 - val_sparse_categorical_crossentropy: 0.0732 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.1070\n",
      "Epoch 280/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1665 - sparse_categorical_crossentropy: 0.0687 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0978 - val_loss: 0.1671 - val_sparse_categorical_crossentropy: 0.0644 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.1028\n",
      "Epoch 281/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1686 - sparse_categorical_crossentropy: 0.0715 - sparse_categorical_accuracy: 0.9737 - scaled_adversarial_loss: 0.0971 - val_loss: 0.1621 - val_sparse_categorical_crossentropy: 0.0708 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0913\n",
      "Epoch 282/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1769 - sparse_categorical_crossentropy: 0.0777 - sparse_categorical_accuracy: 0.9735 - scaled_adversarial_loss: 0.0992 - val_loss: 0.1803 - val_sparse_categorical_crossentropy: 0.0765 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.1039\n",
      "Epoch 283/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1978 - sparse_categorical_crossentropy: 0.0981 - sparse_categorical_accuracy: 0.9655 - scaled_adversarial_loss: 0.0997 - val_loss: 0.1582 - val_sparse_categorical_crossentropy: 0.0684 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0898\n",
      "Epoch 284/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1830 - sparse_categorical_crossentropy: 0.0840 - sparse_categorical_accuracy: 0.9732 - scaled_adversarial_loss: 0.0990 - val_loss: 0.1801 - val_sparse_categorical_crossentropy: 0.0707 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.1094\n",
      "Epoch 285/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.1936 - sparse_categorical_crossentropy: 0.0886 - sparse_categorical_accuracy: 0.9687 - scaled_adversarial_loss: 0.1050 - val_loss: 0.1693 - val_sparse_categorical_crossentropy: 0.0682 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.1010\n",
      "Epoch 286/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1864 - sparse_categorical_crossentropy: 0.0855 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.1009 - val_loss: 0.1660 - val_sparse_categorical_crossentropy: 0.0719 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0941\n",
      "Epoch 287/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1948 - sparse_categorical_crossentropy: 0.0899 - sparse_categorical_accuracy: 0.9708 - scaled_adversarial_loss: 0.1049 - val_loss: 0.1811 - val_sparse_categorical_crossentropy: 0.0936 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.0875\n",
      "Epoch 288/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1824 - sparse_categorical_crossentropy: 0.0814 - sparse_categorical_accuracy: 0.9711 - scaled_adversarial_loss: 0.1010 - val_loss: 0.1726 - val_sparse_categorical_crossentropy: 0.0795 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0930\n",
      "Epoch 289/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1690 - sparse_categorical_crossentropy: 0.0723 - sparse_categorical_accuracy: 0.9757 - scaled_adversarial_loss: 0.0967 - val_loss: 0.1550 - val_sparse_categorical_crossentropy: 0.0602 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0948\n",
      "Epoch 290/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1745 - sparse_categorical_crossentropy: 0.0710 - sparse_categorical_accuracy: 0.9752 - scaled_adversarial_loss: 0.1035 - val_loss: 0.2215 - val_sparse_categorical_crossentropy: 0.1225 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0990\n",
      "Epoch 291/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1816 - sparse_categorical_crossentropy: 0.0859 - sparse_categorical_accuracy: 0.9701 - scaled_adversarial_loss: 0.0957 - val_loss: 0.1628 - val_sparse_categorical_crossentropy: 0.0740 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0889\n",
      "Epoch 292/1000\n",
      "9/9 [==============================] - 3s 390ms/step - loss: 0.1854 - sparse_categorical_crossentropy: 0.0842 - sparse_categorical_accuracy: 0.9725 - scaled_adversarial_loss: 0.1012 - val_loss: 0.1658 - val_sparse_categorical_crossentropy: 0.0664 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0994\n",
      "Epoch 293/1000\n",
      "9/9 [==============================] - 3s 375ms/step - loss: 0.1731 - sparse_categorical_crossentropy: 0.0793 - sparse_categorical_accuracy: 0.9737 - scaled_adversarial_loss: 0.0938 - val_loss: 0.1465 - val_sparse_categorical_crossentropy: 0.0592 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0873\n",
      "Epoch 294/1000\n",
      "9/9 [==============================] - 3s 387ms/step - loss: 0.1603 - sparse_categorical_crossentropy: 0.0618 - sparse_categorical_accuracy: 0.9757 - scaled_adversarial_loss: 0.0985 - val_loss: 0.1617 - val_sparse_categorical_crossentropy: 0.0651 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0966\n",
      "Epoch 295/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1634 - sparse_categorical_crossentropy: 0.0697 - sparse_categorical_accuracy: 0.9740 - scaled_adversarial_loss: 0.0937 - val_loss: 0.1431 - val_sparse_categorical_crossentropy: 0.0606 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0825\n",
      "Epoch 296/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.1552 - sparse_categorical_crossentropy: 0.0632 - sparse_categorical_accuracy: 0.9747 - scaled_adversarial_loss: 0.0920 - val_loss: 0.1927 - val_sparse_categorical_crossentropy: 0.0985 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0942\n",
      "Epoch 297/1000\n",
      "9/9 [==============================] - 3s 391ms/step - loss: 0.1593 - sparse_categorical_crossentropy: 0.0640 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0953 - val_loss: 0.1452 - val_sparse_categorical_crossentropy: 0.0605 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0847\n",
      "Epoch 298/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1480 - sparse_categorical_crossentropy: 0.0579 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0902 - val_loss: 0.1589 - val_sparse_categorical_crossentropy: 0.0846 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0742\n",
      "Epoch 299/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1404 - sparse_categorical_crossentropy: 0.0550 - sparse_categorical_accuracy: 0.9805 - scaled_adversarial_loss: 0.0854 - val_loss: 0.1575 - val_sparse_categorical_crossentropy: 0.0670 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0905\n",
      "Epoch 300/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1573 - sparse_categorical_crossentropy: 0.0687 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1386 - val_sparse_categorical_crossentropy: 0.0578 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0808\n",
      "Epoch 301/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1646 - sparse_categorical_crossentropy: 0.0697 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0949 - val_loss: 0.1643 - val_sparse_categorical_crossentropy: 0.0650 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0993\n",
      "Epoch 302/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1548 - sparse_categorical_crossentropy: 0.0591 - sparse_categorical_accuracy: 0.9776 - scaled_adversarial_loss: 0.0956 - val_loss: 0.1551 - val_sparse_categorical_crossentropy: 0.0742 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0808\n",
      "Epoch 303/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1556 - sparse_categorical_crossentropy: 0.0616 - sparse_categorical_accuracy: 0.9776 - scaled_adversarial_loss: 0.0939 - val_loss: 0.1790 - val_sparse_categorical_crossentropy: 0.0730 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.1060\n",
      "Epoch 304/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1669 - sparse_categorical_crossentropy: 0.0670 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.1000 - val_loss: 0.1653 - val_sparse_categorical_crossentropy: 0.0817 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.0836\n",
      "Epoch 305/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1719 - sparse_categorical_crossentropy: 0.0721 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0998 - val_loss: 0.1458 - val_sparse_categorical_crossentropy: 0.0641 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 306/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1575 - sparse_categorical_crossentropy: 0.0655 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0920 - val_loss: 0.1519 - val_sparse_categorical_crossentropy: 0.0572 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0947\n",
      "Epoch 307/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1547 - sparse_categorical_crossentropy: 0.0576 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0971 - val_loss: 0.1732 - val_sparse_categorical_crossentropy: 0.0644 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.1088\n",
      "Epoch 308/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1581 - sparse_categorical_crossentropy: 0.0617 - sparse_categorical_accuracy: 0.9785 - scaled_adversarial_loss: 0.0963 - val_loss: 0.1617 - val_sparse_categorical_crossentropy: 0.0670 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0946\n",
      "Epoch 309/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1624 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0980 - val_loss: 0.1599 - val_sparse_categorical_crossentropy: 0.0586 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.1013\n",
      "Epoch 310/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1546 - sparse_categorical_crossentropy: 0.0601 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0945 - val_loss: 0.1462 - val_sparse_categorical_crossentropy: 0.0570 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0892\n",
      "Epoch 311/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1617 - sparse_categorical_crossentropy: 0.0702 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0915 - val_loss: 0.1405 - val_sparse_categorical_crossentropy: 0.0534 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0871\n",
      "Epoch 312/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1625 - sparse_categorical_crossentropy: 0.0680 - sparse_categorical_accuracy: 0.9754 - scaled_adversarial_loss: 0.0945 - val_loss: 0.1481 - val_sparse_categorical_crossentropy: 0.0710 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0771\n",
      "Epoch 313/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1539 - sparse_categorical_crossentropy: 0.0617 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0922 - val_loss: 0.1520 - val_sparse_categorical_crossentropy: 0.0571 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0949\n",
      "Epoch 314/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1461 - sparse_categorical_crossentropy: 0.0553 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0907 - val_loss: 0.1476 - val_sparse_categorical_crossentropy: 0.0635 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 315/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1499 - sparse_categorical_crossentropy: 0.0588 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0911 - val_loss: 0.1464 - val_sparse_categorical_crossentropy: 0.0629 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0836\n",
      "Epoch 316/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1472 - sparse_categorical_crossentropy: 0.0578 - sparse_categorical_accuracy: 0.9793 - scaled_adversarial_loss: 0.0894 - val_loss: 0.1676 - val_sparse_categorical_crossentropy: 0.0685 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0991\n",
      "Epoch 317/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.1438 - sparse_categorical_crossentropy: 0.0570 - sparse_categorical_accuracy: 0.9785 - scaled_adversarial_loss: 0.0868 - val_loss: 0.1601 - val_sparse_categorical_crossentropy: 0.0621 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0980\n",
      "Epoch 318/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1574 - sparse_categorical_crossentropy: 0.0628 - sparse_categorical_accuracy: 0.9759 - scaled_adversarial_loss: 0.0946 - val_loss: 0.1479 - val_sparse_categorical_crossentropy: 0.0632 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0846\n",
      "Epoch 319/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1433 - sparse_categorical_crossentropy: 0.0524 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0909 - val_loss: 0.1399 - val_sparse_categorical_crossentropy: 0.0608 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0791\n",
      "Epoch 320/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1382 - sparse_categorical_crossentropy: 0.0549 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0833 - val_loss: 0.1412 - val_sparse_categorical_crossentropy: 0.0608 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0804\n",
      "Epoch 321/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1633 - sparse_categorical_crossentropy: 0.0656 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0977 - val_loss: 0.1462 - val_sparse_categorical_crossentropy: 0.0684 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0779\n",
      "Epoch 322/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1543 - sparse_categorical_crossentropy: 0.0620 - sparse_categorical_accuracy: 0.9776 - scaled_adversarial_loss: 0.0922 - val_loss: 0.1529 - val_sparse_categorical_crossentropy: 0.0644 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0884\n",
      "Epoch 323/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1496 - sparse_categorical_crossentropy: 0.0547 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0948 - val_loss: 0.1389 - val_sparse_categorical_crossentropy: 0.0570 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0819\n",
      "Epoch 324/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.1544 - sparse_categorical_crossentropy: 0.0631 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0914 - val_loss: 0.1433 - val_sparse_categorical_crossentropy: 0.0599 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0834\n",
      "Epoch 325/1000\n",
      "9/9 [==============================] - 3s 392ms/step - loss: 0.1413 - sparse_categorical_crossentropy: 0.0517 - sparse_categorical_accuracy: 0.9800 - scaled_adversarial_loss: 0.0897 - val_loss: 0.1509 - val_sparse_categorical_crossentropy: 0.0589 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0920\n",
      "Epoch 326/1000\n",
      "9/9 [==============================] - 4s 463ms/step - loss: 0.1408 - sparse_categorical_crossentropy: 0.0559 - sparse_categorical_accuracy: 0.9783 - scaled_adversarial_loss: 0.0849 - val_loss: 0.1627 - val_sparse_categorical_crossentropy: 0.0653 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0974\n",
      "Epoch 327/1000\n",
      "9/9 [==============================] - 4s 392ms/step - loss: 0.1570 - sparse_categorical_crossentropy: 0.0643 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0928 - val_loss: 0.1708 - val_sparse_categorical_crossentropy: 0.0627 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.1081\n",
      "Epoch 328/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1552 - sparse_categorical_crossentropy: 0.0621 - sparse_categorical_accuracy: 0.9771 - scaled_adversarial_loss: 0.0931 - val_loss: 0.1944 - val_sparse_categorical_crossentropy: 0.0888 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.1056\n",
      "Epoch 329/1000\n",
      "9/9 [==============================] - 3s 390ms/step - loss: 0.1462 - sparse_categorical_crossentropy: 0.0543 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0919 - val_loss: 0.1357 - val_sparse_categorical_crossentropy: 0.0683 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0674\n",
      "Epoch 330/1000\n",
      "9/9 [==============================] - 4s 394ms/step - loss: 0.1426 - sparse_categorical_crossentropy: 0.0550 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0876 - val_loss: 0.1354 - val_sparse_categorical_crossentropy: 0.0643 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 331/1000\n",
      "9/9 [==============================] - 4s 398ms/step - loss: 0.1523 - sparse_categorical_crossentropy: 0.0574 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0949 - val_loss: 0.1676 - val_sparse_categorical_crossentropy: 0.0771 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0905\n",
      "Epoch 332/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1461 - sparse_categorical_crossentropy: 0.0533 - sparse_categorical_accuracy: 0.9795 - scaled_adversarial_loss: 0.0928 - val_loss: 0.1565 - val_sparse_categorical_crossentropy: 0.0671 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0895\n",
      "Epoch 333/1000\n",
      "9/9 [==============================] - 4s 406ms/step - loss: 0.1431 - sparse_categorical_crossentropy: 0.0526 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0905 - val_loss: 0.1402 - val_sparse_categorical_crossentropy: 0.0539 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0863\n",
      "Epoch 334/1000\n",
      "9/9 [==============================] - 3s 393ms/step - loss: 0.1520 - sparse_categorical_crossentropy: 0.0631 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0888 - val_loss: 0.1654 - val_sparse_categorical_crossentropy: 0.0763 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0891\n",
      "Epoch 335/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1442 - sparse_categorical_crossentropy: 0.0533 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0909 - val_loss: 0.1474 - val_sparse_categorical_crossentropy: 0.0589 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0885\n",
      "Epoch 336/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1492 - sparse_categorical_crossentropy: 0.0562 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0930 - val_loss: 0.1446 - val_sparse_categorical_crossentropy: 0.0564 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0882\n",
      "Epoch 337/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1427 - sparse_categorical_crossentropy: 0.0548 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0879 - val_loss: 0.1535 - val_sparse_categorical_crossentropy: 0.0711 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0824\n",
      "Epoch 338/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1400 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0877 - val_loss: 0.1288 - val_sparse_categorical_crossentropy: 0.0523 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 339/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1513 - sparse_categorical_crossentropy: 0.0595 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0918 - val_loss: 0.1229 - val_sparse_categorical_crossentropy: 0.0559 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0671\n",
      "Epoch 340/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1458 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0898 - val_loss: 0.1357 - val_sparse_categorical_crossentropy: 0.0575 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0782\n",
      "Epoch 341/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1390 - sparse_categorical_crossentropy: 0.0510 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0880 - val_loss: 0.1580 - val_sparse_categorical_crossentropy: 0.0643 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0936\n",
      "Epoch 342/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1499 - sparse_categorical_crossentropy: 0.0562 - sparse_categorical_accuracy: 0.9761 - scaled_adversarial_loss: 0.0937 - val_loss: 0.1392 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0901\n",
      "Epoch 343/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1524 - sparse_categorical_crossentropy: 0.0599 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0925 - val_loss: 0.1448 - val_sparse_categorical_crossentropy: 0.0624 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0824\n",
      "Epoch 344/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1511 - sparse_categorical_crossentropy: 0.0599 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0911 - val_loss: 0.1557 - val_sparse_categorical_crossentropy: 0.0582 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0975\n",
      "Epoch 345/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1512 - sparse_categorical_crossentropy: 0.0619 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0893 - val_loss: 0.1784 - val_sparse_categorical_crossentropy: 0.0835 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0949\n",
      "Epoch 346/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1589 - sparse_categorical_crossentropy: 0.0691 - sparse_categorical_accuracy: 0.9764 - scaled_adversarial_loss: 0.0898 - val_loss: 0.1280 - val_sparse_categorical_crossentropy: 0.0628 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0653\n",
      "Epoch 347/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1450 - sparse_categorical_crossentropy: 0.0518 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0932 - val_loss: 0.1224 - val_sparse_categorical_crossentropy: 0.0490 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0735\n",
      "Epoch 348/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.1538 - sparse_categorical_crossentropy: 0.0543 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0995 - val_loss: 0.1535 - val_sparse_categorical_crossentropy: 0.0546 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0989\n",
      "Epoch 349/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1551 - sparse_categorical_crossentropy: 0.0639 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0913 - val_loss: 0.1708 - val_sparse_categorical_crossentropy: 0.0666 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.1042\n",
      "Epoch 350/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1575 - sparse_categorical_crossentropy: 0.0612 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0963 - val_loss: 0.1555 - val_sparse_categorical_crossentropy: 0.0912 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0643\n",
      "Epoch 351/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.1598 - sparse_categorical_crossentropy: 0.0606 - sparse_categorical_accuracy: 0.9759 - scaled_adversarial_loss: 0.0992 - val_loss: 0.1479 - val_sparse_categorical_crossentropy: 0.0563 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0915\n",
      "Epoch 352/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1550 - sparse_categorical_crossentropy: 0.0612 - sparse_categorical_accuracy: 0.9814 - scaled_adversarial_loss: 0.0939 - val_loss: 0.1426 - val_sparse_categorical_crossentropy: 0.0651 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0775\n",
      "Epoch 353/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.1379 - sparse_categorical_crossentropy: 0.0491 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0889 - val_loss: 0.1433 - val_sparse_categorical_crossentropy: 0.0564 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0869\n",
      "Epoch 354/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1460 - sparse_categorical_crossentropy: 0.0554 - sparse_categorical_accuracy: 0.9793 - scaled_adversarial_loss: 0.0906 - val_loss: 0.1285 - val_sparse_categorical_crossentropy: 0.0646 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0638\n",
      "Epoch 355/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1422 - sparse_categorical_crossentropy: 0.0527 - sparse_categorical_accuracy: 0.9805 - scaled_adversarial_loss: 0.0896 - val_loss: 0.1285 - val_sparse_categorical_crossentropy: 0.0640 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0645\n",
      "Epoch 356/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1328 - sparse_categorical_crossentropy: 0.0540 - sparse_categorical_accuracy: 0.9793 - scaled_adversarial_loss: 0.0788 - val_loss: 0.1330 - val_sparse_categorical_crossentropy: 0.0585 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0745\n",
      "Epoch 357/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.1383 - sparse_categorical_crossentropy: 0.0483 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0900 - val_loss: 0.1392 - val_sparse_categorical_crossentropy: 0.0553 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0839\n",
      "Epoch 358/1000\n",
      "9/9 [==============================] - 3s 383ms/step - loss: 0.1373 - sparse_categorical_crossentropy: 0.0515 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0858 - val_loss: 0.1269 - val_sparse_categorical_crossentropy: 0.0558 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 359/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1520 - sparse_categorical_crossentropy: 0.0614 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0906 - val_loss: 0.1429 - val_sparse_categorical_crossentropy: 0.0519 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0910\n",
      "Epoch 360/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1485 - sparse_categorical_crossentropy: 0.0574 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0911 - val_loss: 0.1250 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0750\n",
      "Epoch 361/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1376 - sparse_categorical_crossentropy: 0.0489 - sparse_categorical_accuracy: 0.9805 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1462 - val_sparse_categorical_crossentropy: 0.0780 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0682\n",
      "Epoch 362/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1381 - sparse_categorical_crossentropy: 0.0521 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1307 - val_sparse_categorical_crossentropy: 0.0565 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0743\n",
      "Epoch 363/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1381 - sparse_categorical_crossentropy: 0.0491 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0890 - val_loss: 0.1482 - val_sparse_categorical_crossentropy: 0.0568 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0914\n",
      "Epoch 364/1000\n",
      "9/9 [==============================] - 3s 381ms/step - loss: 0.1557 - sparse_categorical_crossentropy: 0.0651 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0906 - val_loss: 0.1317 - val_sparse_categorical_crossentropy: 0.0606 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0712\n",
      "Epoch 365/1000\n",
      "9/9 [==============================] - 4s 398ms/step - loss: 0.1478 - sparse_categorical_crossentropy: 0.0568 - sparse_categorical_accuracy: 0.9800 - scaled_adversarial_loss: 0.0911 - val_loss: 0.1579 - val_sparse_categorical_crossentropy: 0.0650 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0930\n",
      "Epoch 366/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1462 - sparse_categorical_crossentropy: 0.0570 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0893 - val_loss: 0.1408 - val_sparse_categorical_crossentropy: 0.0625 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0783\n",
      "Epoch 367/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1365 - sparse_categorical_crossentropy: 0.0479 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1406 - val_sparse_categorical_crossentropy: 0.0510 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0896\n",
      "Epoch 368/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1374 - sparse_categorical_crossentropy: 0.0488 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1372 - val_sparse_categorical_crossentropy: 0.0688 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0684\n",
      "Epoch 369/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1381 - sparse_categorical_crossentropy: 0.0497 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0884 - val_loss: 0.1366 - val_sparse_categorical_crossentropy: 0.0697 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0670\n",
      "Epoch 370/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1464 - sparse_categorical_crossentropy: 0.0505 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0960 - val_loss: 0.1346 - val_sparse_categorical_crossentropy: 0.0632 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0714\n",
      "Epoch 371/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1487 - sparse_categorical_crossentropy: 0.0585 - sparse_categorical_accuracy: 0.9776 - scaled_adversarial_loss: 0.0902 - val_loss: 0.1466 - val_sparse_categorical_crossentropy: 0.0505 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0960\n",
      "Epoch 372/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1509 - sparse_categorical_crossentropy: 0.0545 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0964 - val_loss: 0.1464 - val_sparse_categorical_crossentropy: 0.0697 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0767\n",
      "Epoch 373/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1433 - sparse_categorical_crossentropy: 0.0511 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0922 - val_loss: 0.1349 - val_sparse_categorical_crossentropy: 0.0603 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0746\n",
      "Epoch 374/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1368 - sparse_categorical_crossentropy: 0.0505 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0863 - val_loss: 0.1313 - val_sparse_categorical_crossentropy: 0.0516 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0798\n",
      "Epoch 375/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1451 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0891 - val_loss: 0.1245 - val_sparse_categorical_crossentropy: 0.0461 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0784\n",
      "Epoch 376/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1365 - sparse_categorical_crossentropy: 0.0501 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0863 - val_loss: 0.1406 - val_sparse_categorical_crossentropy: 0.0607 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0799\n",
      "Epoch 377/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1391 - sparse_categorical_crossentropy: 0.0499 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0892 - val_loss: 0.1356 - val_sparse_categorical_crossentropy: 0.0682 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0674\n",
      "Epoch 378/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.1355 - sparse_categorical_crossentropy: 0.0453 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0902 - val_loss: 0.1420 - val_sparse_categorical_crossentropy: 0.0585 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0835\n",
      "Epoch 379/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1339 - sparse_categorical_crossentropy: 0.0508 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0831 - val_loss: 0.1197 - val_sparse_categorical_crossentropy: 0.0483 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0713\n",
      "Epoch 380/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1415 - sparse_categorical_crossentropy: 0.0459 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0955 - val_loss: 0.1371 - val_sparse_categorical_crossentropy: 0.0518 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0853\n",
      "Epoch 381/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1346 - sparse_categorical_crossentropy: 0.0479 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1493 - val_sparse_categorical_crossentropy: 0.0549 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0944\n",
      "Epoch 382/1000\n",
      "9/9 [==============================] - 3s 395ms/step - loss: 0.1336 - sparse_categorical_crossentropy: 0.0460 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0876 - val_loss: 0.1534 - val_sparse_categorical_crossentropy: 0.0648 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0886\n",
      "Epoch 383/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1328 - sparse_categorical_crossentropy: 0.0474 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0854 - val_loss: 0.1460 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0934\n",
      "Epoch 384/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1407 - sparse_categorical_crossentropy: 0.0501 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0906 - val_loss: 0.1337 - val_sparse_categorical_crossentropy: 0.0560 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0776\n",
      "Epoch 385/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1528 - sparse_categorical_crossentropy: 0.0654 - sparse_categorical_accuracy: 0.9785 - scaled_adversarial_loss: 0.0874 - val_loss: 0.1351 - val_sparse_categorical_crossentropy: 0.0432 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0919\n",
      "Epoch 386/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1438 - sparse_categorical_crossentropy: 0.0564 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0874 - val_loss: 0.1625 - val_sparse_categorical_crossentropy: 0.0677 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0949\n",
      "Epoch 387/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1426 - sparse_categorical_crossentropy: 0.0525 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0901 - val_loss: 0.1580 - val_sparse_categorical_crossentropy: 0.0592 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0988\n",
      "Epoch 388/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1325 - sparse_categorical_crossentropy: 0.0471 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0854 - val_loss: 0.1334 - val_sparse_categorical_crossentropy: 0.0504 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0830\n",
      "Epoch 389/1000\n",
      "9/9 [==============================] - 4s 413ms/step - loss: 0.1439 - sparse_categorical_crossentropy: 0.0556 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0883 - val_loss: 0.1361 - val_sparse_categorical_crossentropy: 0.0520 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0841\n",
      "Epoch 390/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1453 - sparse_categorical_crossentropy: 0.0511 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0942 - val_loss: 0.1268 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0757\n",
      "Epoch 391/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1377 - sparse_categorical_crossentropy: 0.0485 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0892 - val_loss: 0.1373 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0832\n",
      "Epoch 392/1000\n",
      "9/9 [==============================] - 3s 383ms/step - loss: 0.1354 - sparse_categorical_crossentropy: 0.0498 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0856 - val_loss: 0.1219 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 393/1000\n",
      "9/9 [==============================] - 4s 395ms/step - loss: 0.1242 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0851 - val_loss: 0.1226 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0764\n",
      "Epoch 394/1000\n",
      "9/9 [==============================] - 4s 402ms/step - loss: 0.1312 - sparse_categorical_crossentropy: 0.0488 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1417 - val_sparse_categorical_crossentropy: 0.0498 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0920\n",
      "Epoch 395/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.1448 - sparse_categorical_crossentropy: 0.0562 - sparse_categorical_accuracy: 0.9800 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1603 - val_sparse_categorical_crossentropy: 0.0602 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.1001\n",
      "Epoch 396/1000\n",
      "9/9 [==============================] - 4s 417ms/step - loss: 0.1515 - sparse_categorical_crossentropy: 0.0630 - sparse_categorical_accuracy: 0.9793 - scaled_adversarial_loss: 0.0885 - val_loss: 0.1183 - val_sparse_categorical_crossentropy: 0.0486 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0697\n",
      "Epoch 397/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1428 - sparse_categorical_crossentropy: 0.0545 - sparse_categorical_accuracy: 0.9781 - scaled_adversarial_loss: 0.0882 - val_loss: 0.1414 - val_sparse_categorical_crossentropy: 0.0523 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0892\n",
      "Epoch 398/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1390 - sparse_categorical_crossentropy: 0.0532 - sparse_categorical_accuracy: 0.9805 - scaled_adversarial_loss: 0.0858 - val_loss: 0.1531 - val_sparse_categorical_crossentropy: 0.0590 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0941\n",
      "Epoch 399/1000\n",
      "9/9 [==============================] - 4s 400ms/step - loss: 0.1360 - sparse_categorical_crossentropy: 0.0522 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0838 - val_loss: 0.1268 - val_sparse_categorical_crossentropy: 0.0476 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0792\n",
      "Epoch 400/1000\n",
      "9/9 [==============================] - 4s 395ms/step - loss: 0.1392 - sparse_categorical_crossentropy: 0.0510 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0882 - val_loss: 0.1527 - val_sparse_categorical_crossentropy: 0.0604 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0923\n",
      "Epoch 401/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1563 - sparse_categorical_crossentropy: 0.0669 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0894 - val_loss: 0.1384 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0881\n",
      "Epoch 402/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1467 - sparse_categorical_crossentropy: 0.0565 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0903 - val_loss: 0.1551 - val_sparse_categorical_crossentropy: 0.0644 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0906\n",
      "Epoch 403/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1483 - sparse_categorical_crossentropy: 0.0584 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0899 - val_loss: 0.1254 - val_sparse_categorical_crossentropy: 0.0468 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0787\n",
      "Epoch 404/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1467 - sparse_categorical_crossentropy: 0.0566 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0901 - val_loss: 0.1390 - val_sparse_categorical_crossentropy: 0.0532 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0858\n",
      "Epoch 405/1000\n",
      "9/9 [==============================] - 4s 433ms/step - loss: 0.1427 - sparse_categorical_crossentropy: 0.0548 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0879 - val_loss: 0.1559 - val_sparse_categorical_crossentropy: 0.0683 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0876\n",
      "Epoch 406/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1376 - sparse_categorical_crossentropy: 0.0552 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1062 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 407/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1540 - sparse_categorical_crossentropy: 0.0696 - sparse_categorical_accuracy: 0.9776 - scaled_adversarial_loss: 0.0843 - val_loss: 0.1549 - val_sparse_categorical_crossentropy: 0.0739 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0810\n",
      "Epoch 408/1000\n",
      "9/9 [==============================] - 3s 383ms/step - loss: 0.1565 - sparse_categorical_crossentropy: 0.0678 - sparse_categorical_accuracy: 0.9761 - scaled_adversarial_loss: 0.0887 - val_loss: 0.1479 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0982\n",
      "Epoch 409/1000\n",
      "9/9 [==============================] - 3s 376ms/step - loss: 0.1715 - sparse_categorical_crossentropy: 0.0786 - sparse_categorical_accuracy: 0.9728 - scaled_adversarial_loss: 0.0928 - val_loss: 0.1406 - val_sparse_categorical_crossentropy: 0.0531 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0875\n",
      "Epoch 410/1000\n",
      "9/9 [==============================] - 3s 393ms/step - loss: 0.1800 - sparse_categorical_crossentropy: 0.0826 - sparse_categorical_accuracy: 0.9703 - scaled_adversarial_loss: 0.0974 - val_loss: 0.1538 - val_sparse_categorical_crossentropy: 0.0630 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0908\n",
      "Epoch 411/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1378 - sparse_categorical_crossentropy: 0.0512 - sparse_categorical_accuracy: 0.9785 - scaled_adversarial_loss: 0.0866 - val_loss: 0.1558 - val_sparse_categorical_crossentropy: 0.0653 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0905\n",
      "Epoch 412/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1553 - sparse_categorical_crossentropy: 0.0562 - sparse_categorical_accuracy: 0.9788 - scaled_adversarial_loss: 0.0991 - val_loss: 0.1117 - val_sparse_categorical_crossentropy: 0.0498 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0619\n",
      "Epoch 413/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0468 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0900 - val_loss: 0.1439 - val_sparse_categorical_crossentropy: 0.0643 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0796\n",
      "Epoch 414/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1423 - sparse_categorical_crossentropy: 0.0497 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0926 - val_loss: 0.1206 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0699\n",
      "Epoch 415/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1313 - sparse_categorical_crossentropy: 0.0448 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0866 - val_loss: 0.1447 - val_sparse_categorical_crossentropy: 0.0591 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0855\n",
      "Epoch 416/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1363 - sparse_categorical_crossentropy: 0.0527 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0836 - val_loss: 0.1361 - val_sparse_categorical_crossentropy: 0.0639 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0723\n",
      "Epoch 417/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1500 - sparse_categorical_crossentropy: 0.0593 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0907 - val_loss: 0.1350 - val_sparse_categorical_crossentropy: 0.0573 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0777\n",
      "Epoch 418/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.1500 - sparse_categorical_crossentropy: 0.0591 - sparse_categorical_accuracy: 0.9773 - scaled_adversarial_loss: 0.0909 - val_loss: 0.1454 - val_sparse_categorical_crossentropy: 0.0666 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0788\n",
      "Epoch 419/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1421 - sparse_categorical_crossentropy: 0.0578 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0844 - val_loss: 0.1246 - val_sparse_categorical_crossentropy: 0.0480 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0766\n",
      "Epoch 420/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1409 - sparse_categorical_crossentropy: 0.0499 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0910 - val_loss: 0.1265 - val_sparse_categorical_crossentropy: 0.0616 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0648\n",
      "Epoch 421/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1281 - sparse_categorical_crossentropy: 0.0430 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0851 - val_loss: 0.1315 - val_sparse_categorical_crossentropy: 0.0638 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 422/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1378 - sparse_categorical_crossentropy: 0.0556 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0823 - val_loss: 0.1275 - val_sparse_categorical_crossentropy: 0.0598 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 423/1000\n",
      "9/9 [==============================] - 3s 390ms/step - loss: 0.1271 - sparse_categorical_crossentropy: 0.0396 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0875 - val_loss: 0.1152 - val_sparse_categorical_crossentropy: 0.0459 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0693\n",
      "Epoch 424/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0492 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0854 - val_loss: 0.1246 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 425/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1332 - sparse_categorical_crossentropy: 0.0511 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0821 - val_loss: 0.1464 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0973\n",
      "Epoch 426/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1488 - sparse_categorical_crossentropy: 0.0572 - sparse_categorical_accuracy: 0.9785 - scaled_adversarial_loss: 0.0917 - val_loss: 0.1373 - val_sparse_categorical_crossentropy: 0.0671 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0701\n",
      "Epoch 427/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.1461 - sparse_categorical_crossentropy: 0.0564 - sparse_categorical_accuracy: 0.9793 - scaled_adversarial_loss: 0.0896 - val_loss: 0.1287 - val_sparse_categorical_crossentropy: 0.0556 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0731\n",
      "Epoch 428/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1323 - sparse_categorical_crossentropy: 0.0464 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1223 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0780\n",
      "Epoch 429/1000\n",
      "9/9 [==============================] - 4s 399ms/step - loss: 0.1252 - sparse_categorical_crossentropy: 0.0421 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0831 - val_loss: 0.1309 - val_sparse_categorical_crossentropy: 0.0483 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0825\n",
      "Epoch 430/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.1309 - sparse_categorical_crossentropy: 0.0466 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0843 - val_loss: 0.1164 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0697\n",
      "Epoch 431/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0522 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0848 - val_loss: 0.1222 - val_sparse_categorical_crossentropy: 0.0550 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0671\n",
      "Epoch 432/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1339 - sparse_categorical_crossentropy: 0.0483 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0856 - val_loss: 0.1371 - val_sparse_categorical_crossentropy: 0.0544 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0827\n",
      "Epoch 433/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1422 - sparse_categorical_crossentropy: 0.0491 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0931 - val_loss: 0.1312 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0829\n",
      "Epoch 434/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1307 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0879 - val_loss: 0.1199 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0732\n",
      "Epoch 435/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1243 - sparse_categorical_crossentropy: 0.0397 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0846 - val_loss: 0.1377 - val_sparse_categorical_crossentropy: 0.0524 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0853\n",
      "Epoch 436/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1242 - sparse_categorical_crossentropy: 0.0432 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0810 - val_loss: 0.1359 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0818\n",
      "Epoch 437/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1324 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0887 - val_loss: 0.1176 - val_sparse_categorical_crossentropy: 0.0487 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0689\n",
      "Epoch 438/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1235 - sparse_categorical_crossentropy: 0.0386 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0849 - val_loss: 0.1223 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0751\n",
      "Epoch 439/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0862 - val_loss: 0.1221 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0710\n",
      "Epoch 440/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1212 - sparse_categorical_crossentropy: 0.0429 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0784 - val_loss: 0.1493 - val_sparse_categorical_crossentropy: 0.0596 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0897\n",
      "Epoch 441/1000\n",
      "9/9 [==============================] - 3s 375ms/step - loss: 0.1437 - sparse_categorical_crossentropy: 0.0558 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0879 - val_loss: 0.1080 - val_sparse_categorical_crossentropy: 0.0464 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0615\n",
      "Epoch 442/1000\n",
      "9/9 [==============================] - 4s 370ms/step - loss: 0.1279 - sparse_categorical_crossentropy: 0.0422 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0857 - val_loss: 0.1413 - val_sparse_categorical_crossentropy: 0.0546 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0867\n",
      "Epoch 443/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1169 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0772 - val_loss: 0.1388 - val_sparse_categorical_crossentropy: 0.0539 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0850\n",
      "Epoch 444/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1291 - sparse_categorical_crossentropy: 0.0413 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0878 - val_loss: 0.1278 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 445/1000\n",
      "9/9 [==============================] - 3s 388ms/step - loss: 0.1202 - sparse_categorical_crossentropy: 0.0394 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0809 - val_loss: 0.1323 - val_sparse_categorical_crossentropy: 0.0556 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0768\n",
      "Epoch 446/1000\n",
      "9/9 [==============================] - 3s 388ms/step - loss: 0.1321 - sparse_categorical_crossentropy: 0.0480 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0841 - val_loss: 0.1158 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0691\n",
      "Epoch 447/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1350 - sparse_categorical_crossentropy: 0.0487 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0863 - val_loss: 0.1355 - val_sparse_categorical_crossentropy: 0.0560 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0795\n",
      "Epoch 448/1000\n",
      "9/9 [==============================] - 3s 376ms/step - loss: 0.1335 - sparse_categorical_crossentropy: 0.0481 - sparse_categorical_accuracy: 0.9831 - scaled_adversarial_loss: 0.0854 - val_loss: 0.1251 - val_sparse_categorical_crossentropy: 0.0470 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0782\n",
      "Epoch 449/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0443 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0838 - val_loss: 0.1199 - val_sparse_categorical_crossentropy: 0.0482 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 450/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0462 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0883 - val_loss: 0.1292 - val_sparse_categorical_crossentropy: 0.0560 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0732\n",
      "Epoch 451/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1341 - sparse_categorical_crossentropy: 0.0512 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0829 - val_loss: 0.1199 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0673\n",
      "Epoch 452/1000\n",
      "9/9 [==============================] - 3s 376ms/step - loss: 0.1704 - sparse_categorical_crossentropy: 0.0777 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0927 - val_loss: 0.1275 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0760\n",
      "Epoch 453/1000\n",
      "9/9 [==============================] - 4s 409ms/step - loss: 0.1490 - sparse_categorical_crossentropy: 0.0541 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0949 - val_loss: 0.1347 - val_sparse_categorical_crossentropy: 0.0597 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0750\n",
      "Epoch 454/1000\n",
      "9/9 [==============================] - 4s 407ms/step - loss: 0.1349 - sparse_categorical_crossentropy: 0.0502 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0847 - val_loss: 0.1286 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0805\n",
      "Epoch 455/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1307 - sparse_categorical_crossentropy: 0.0448 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1314 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0847\n",
      "Epoch 456/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1297 - sparse_categorical_crossentropy: 0.0430 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0866 - val_loss: 0.1248 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 457/1000\n",
      "9/9 [==============================] - 4s 415ms/step - loss: 0.1259 - sparse_categorical_crossentropy: 0.0393 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0865 - val_loss: 0.1273 - val_sparse_categorical_crossentropy: 0.0492 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0781\n",
      "Epoch 458/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1218 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0801 - val_loss: 0.1141 - val_sparse_categorical_crossentropy: 0.0455 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0685\n",
      "Epoch 459/1000\n",
      "9/9 [==============================] - 4s 428ms/step - loss: 0.1274 - sparse_categorical_crossentropy: 0.0425 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0849 - val_loss: 0.1325 - val_sparse_categorical_crossentropy: 0.0562 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0763\n",
      "Epoch 460/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1236 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0848 - val_loss: 0.1598 - val_sparse_categorical_crossentropy: 0.0740 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0858\n",
      "Epoch 461/1000\n",
      "9/9 [==============================] - 4s 401ms/step - loss: 0.1460 - sparse_categorical_crossentropy: 0.0605 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0856 - val_loss: 0.1364 - val_sparse_categorical_crossentropy: 0.0551 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0814\n",
      "Epoch 462/1000\n",
      "9/9 [==============================] - 4s 412ms/step - loss: 0.1489 - sparse_categorical_crossentropy: 0.0645 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0844 - val_loss: 0.1321 - val_sparse_categorical_crossentropy: 0.0564 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0757\n",
      "Epoch 463/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1507 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9800 - scaled_adversarial_loss: 0.0873 - val_loss: 0.1202 - val_sparse_categorical_crossentropy: 0.0514 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 464/1000\n",
      "9/9 [==============================] - 4s 413ms/step - loss: 0.1489 - sparse_categorical_crossentropy: 0.0622 - sparse_categorical_accuracy: 0.9793 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1254 - val_sparse_categorical_crossentropy: 0.0537 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 465/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1312 - sparse_categorical_crossentropy: 0.0420 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0892 - val_loss: 0.1299 - val_sparse_categorical_crossentropy: 0.0602 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0697\n",
      "Epoch 466/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1209 - sparse_categorical_crossentropy: 0.0474 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0736 - val_loss: 0.1186 - val_sparse_categorical_crossentropy: 0.0538 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0648\n",
      "Epoch 467/1000\n",
      "9/9 [==============================] - 4s 432ms/step - loss: 0.1268 - sparse_categorical_crossentropy: 0.0453 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0815 - val_loss: 0.1158 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0693\n",
      "Epoch 468/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1342 - sparse_categorical_crossentropy: 0.0490 - sparse_categorical_accuracy: 0.9834 - scaled_adversarial_loss: 0.0852 - val_loss: 0.1196 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0722\n",
      "Epoch 469/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1210 - sparse_categorical_crossentropy: 0.0381 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0829 - val_loss: 0.1305 - val_sparse_categorical_crossentropy: 0.0575 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0730\n",
      "Epoch 470/1000\n",
      "9/9 [==============================] - 3s 386ms/step - loss: 0.1410 - sparse_categorical_crossentropy: 0.0542 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0868 - val_loss: 0.1046 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0573\n",
      "Epoch 471/1000\n",
      "9/9 [==============================] - 4s 389ms/step - loss: 0.1219 - sparse_categorical_crossentropy: 0.0408 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0812 - val_loss: 0.1127 - val_sparse_categorical_crossentropy: 0.0464 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0663\n",
      "Epoch 472/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1399 - sparse_categorical_crossentropy: 0.0548 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0851 - val_loss: 0.1204 - val_sparse_categorical_crossentropy: 0.0516 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0689\n",
      "Epoch 473/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0525 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0843 - val_loss: 0.1797 - val_sparse_categorical_crossentropy: 0.0877 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0920\n",
      "Epoch 474/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1524 - sparse_categorical_crossentropy: 0.0642 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0882 - val_loss: 0.1020 - val_sparse_categorical_crossentropy: 0.0490 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 475/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1318 - sparse_categorical_crossentropy: 0.0454 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0864 - val_loss: 0.1373 - val_sparse_categorical_crossentropy: 0.0645 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0728\n",
      "Epoch 476/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1354 - sparse_categorical_crossentropy: 0.0527 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0827 - val_loss: 0.1282 - val_sparse_categorical_crossentropy: 0.0575 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0707\n",
      "Epoch 477/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1444 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0884 - val_loss: 0.1145 - val_sparse_categorical_crossentropy: 0.0465 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0680\n",
      "Epoch 478/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1310 - sparse_categorical_crossentropy: 0.0461 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0850 - val_loss: 0.1250 - val_sparse_categorical_crossentropy: 0.0590 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0660\n",
      "Epoch 479/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1299 - sparse_categorical_crossentropy: 0.0522 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0777 - val_loss: 0.1341 - val_sparse_categorical_crossentropy: 0.0589 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0752\n",
      "Epoch 480/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1392 - sparse_categorical_crossentropy: 0.0513 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0879 - val_loss: 0.1200 - val_sparse_categorical_crossentropy: 0.0456 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0745\n",
      "Epoch 481/1000\n",
      "9/9 [==============================] - 3s 381ms/step - loss: 0.1209 - sparse_categorical_crossentropy: 0.0376 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0833 - val_loss: 0.1143 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0676\n",
      "Epoch 482/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1257 - sparse_categorical_crossentropy: 0.0455 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0803 - val_loss: 0.1382 - val_sparse_categorical_crossentropy: 0.0530 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0852\n",
      "Epoch 483/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1389 - sparse_categorical_crossentropy: 0.0497 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0892 - val_loss: 0.1162 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0681\n",
      "Epoch 484/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1302 - sparse_categorical_crossentropy: 0.0470 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0832 - val_loss: 0.1074 - val_sparse_categorical_crossentropy: 0.0518 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 485/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1183 - sparse_categorical_crossentropy: 0.0386 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0797 - val_loss: 0.1208 - val_sparse_categorical_crossentropy: 0.0576 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0632\n",
      "Epoch 486/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1324 - sparse_categorical_crossentropy: 0.0489 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0835 - val_loss: 0.0997 - val_sparse_categorical_crossentropy: 0.0403 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0594\n",
      "Epoch 487/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1238 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0829 - val_loss: 0.1138 - val_sparse_categorical_crossentropy: 0.0413 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 488/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1222 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0794 - val_loss: 0.1294 - val_sparse_categorical_crossentropy: 0.0522 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0772\n",
      "Epoch 489/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1214 - sparse_categorical_crossentropy: 0.0358 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0856 - val_loss: 0.1248 - val_sparse_categorical_crossentropy: 0.0432 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0815\n",
      "Epoch 490/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1237 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1115 - val_sparse_categorical_crossentropy: 0.0494 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0621\n",
      "Epoch 491/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1244 - sparse_categorical_crossentropy: 0.0415 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1040 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 492/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1349 - sparse_categorical_crossentropy: 0.0456 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0893 - val_loss: 0.1296 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0805\n",
      "Epoch 493/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1243 - sparse_categorical_crossentropy: 0.0463 - sparse_categorical_accuracy: 0.9831 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1210 - val_sparse_categorical_crossentropy: 0.0452 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0759\n",
      "Epoch 494/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1289 - sparse_categorical_crossentropy: 0.0493 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0797 - val_loss: 0.1225 - val_sparse_categorical_crossentropy: 0.0532 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0693\n",
      "Epoch 495/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1350 - sparse_categorical_crossentropy: 0.0530 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0821 - val_loss: 0.1180 - val_sparse_categorical_crossentropy: 0.0418 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0762\n",
      "Epoch 496/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0389 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0812 - val_loss: 0.1108 - val_sparse_categorical_crossentropy: 0.0453 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0655\n",
      "Epoch 497/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1290 - sparse_categorical_crossentropy: 0.0432 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0858 - val_loss: 0.1145 - val_sparse_categorical_crossentropy: 0.0528 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0617\n",
      "Epoch 498/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1243 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0852 - val_loss: 0.1285 - val_sparse_categorical_crossentropy: 0.0546 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0739\n",
      "Epoch 499/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1380 - sparse_categorical_crossentropy: 0.0483 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0897 - val_loss: 0.1234 - val_sparse_categorical_crossentropy: 0.0533 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0702\n",
      "Epoch 500/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1197 - sparse_categorical_crossentropy: 0.0379 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0817 - val_loss: 0.1551 - val_sparse_categorical_crossentropy: 0.0566 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0985\n",
      "Epoch 501/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0446 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1521 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.1084\n",
      "Epoch 502/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0423 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0826 - val_loss: 0.1088 - val_sparse_categorical_crossentropy: 0.0492 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0596\n",
      "Epoch 503/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0763 - val_loss: 0.1096 - val_sparse_categorical_crossentropy: 0.0498 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0598\n",
      "Epoch 504/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1251 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0877 - val_loss: 0.1319 - val_sparse_categorical_crossentropy: 0.0550 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0769\n",
      "Epoch 505/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1413 - sparse_categorical_crossentropy: 0.0575 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0838 - val_loss: 0.1424 - val_sparse_categorical_crossentropy: 0.0627 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 506/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1536 - sparse_categorical_crossentropy: 0.0724 - sparse_categorical_accuracy: 0.9716 - scaled_adversarial_loss: 0.0812 - val_loss: 0.1431 - val_sparse_categorical_crossentropy: 0.0565 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0867\n",
      "Epoch 507/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1404 - sparse_categorical_crossentropy: 0.0535 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0869 - val_loss: 0.1455 - val_sparse_categorical_crossentropy: 0.0701 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0754\n",
      "Epoch 508/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1491 - sparse_categorical_crossentropy: 0.0588 - sparse_categorical_accuracy: 0.9807 - scaled_adversarial_loss: 0.0903 - val_loss: 0.1198 - val_sparse_categorical_crossentropy: 0.0596 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0602\n",
      "Epoch 509/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1452 - sparse_categorical_crossentropy: 0.0564 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0888 - val_loss: 0.1168 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0666\n",
      "Epoch 510/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1336 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0813 - val_loss: 0.1087 - val_sparse_categorical_crossentropy: 0.0474 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 511/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1246 - sparse_categorical_crossentropy: 0.0461 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0785 - val_loss: 0.1094 - val_sparse_categorical_crossentropy: 0.0390 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 512/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1534 - sparse_categorical_crossentropy: 0.0699 - sparse_categorical_accuracy: 0.9797 - scaled_adversarial_loss: 0.0835 - val_loss: 0.0938 - val_sparse_categorical_crossentropy: 0.0407 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0531\n",
      "Epoch 513/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1674 - sparse_categorical_crossentropy: 0.0748 - sparse_categorical_accuracy: 0.9778 - scaled_adversarial_loss: 0.0926 - val_loss: 0.1392 - val_sparse_categorical_crossentropy: 0.0492 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0900\n",
      "Epoch 514/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1551 - sparse_categorical_crossentropy: 0.0573 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0978 - val_loss: 0.1167 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0660\n",
      "Epoch 515/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1272 - sparse_categorical_crossentropy: 0.0415 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0857 - val_loss: 0.1151 - val_sparse_categorical_crossentropy: 0.0477 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0674\n",
      "Epoch 516/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1322 - sparse_categorical_crossentropy: 0.0416 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0906 - val_loss: 0.1137 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0637\n",
      "Epoch 517/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1240 - sparse_categorical_crossentropy: 0.0375 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0865 - val_loss: 0.1022 - val_sparse_categorical_crossentropy: 0.0502 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0520\n",
      "Epoch 518/1000\n",
      "9/9 [==============================] - 3s 378ms/step - loss: 0.1251 - sparse_categorical_crossentropy: 0.0363 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0887 - val_loss: 0.1102 - val_sparse_categorical_crossentropy: 0.0401 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0701\n",
      "Epoch 519/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1308 - sparse_categorical_crossentropy: 0.0407 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0900 - val_loss: 0.1125 - val_sparse_categorical_crossentropy: 0.0505 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 520/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.1187 - sparse_categorical_crossentropy: 0.0382 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0805 - val_loss: 0.1093 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0586\n",
      "Epoch 521/1000\n",
      "9/9 [==============================] - 4s 414ms/step - loss: 0.1160 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1330 - val_sparse_categorical_crossentropy: 0.0495 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0835\n",
      "Epoch 522/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0441 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0808 - val_loss: 0.1059 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0622\n",
      "Epoch 523/1000\n",
      "9/9 [==============================] - 3s 383ms/step - loss: 0.1204 - sparse_categorical_crossentropy: 0.0419 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0786 - val_loss: 0.1556 - val_sparse_categorical_crossentropy: 0.0802 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0755\n",
      "Epoch 524/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1254 - sparse_categorical_crossentropy: 0.0399 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0856 - val_loss: 0.1256 - val_sparse_categorical_crossentropy: 0.0471 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0785\n",
      "Epoch 525/1000\n",
      "9/9 [==============================] - 4s 432ms/step - loss: 0.1247 - sparse_categorical_crossentropy: 0.0390 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0857 - val_loss: 0.1267 - val_sparse_categorical_crossentropy: 0.0590 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0677\n",
      "Epoch 526/1000\n",
      "9/9 [==============================] - 4s 399ms/step - loss: 0.1180 - sparse_categorical_crossentropy: 0.0387 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0792 - val_loss: 0.1041 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0595\n",
      "Epoch 527/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1240 - sparse_categorical_crossentropy: 0.0449 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0791 - val_loss: 0.1202 - val_sparse_categorical_crossentropy: 0.0464 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0738\n",
      "Epoch 528/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0393 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0796 - val_loss: 0.1269 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0788\n",
      "Epoch 529/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1211 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0843 - val_loss: 0.1138 - val_sparse_categorical_crossentropy: 0.0396 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0743\n",
      "Epoch 530/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1208 - sparse_categorical_crossentropy: 0.0430 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0778 - val_loss: 0.0955 - val_sparse_categorical_crossentropy: 0.0386 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0569\n",
      "Epoch 531/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0470 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0837 - val_loss: 0.1270 - val_sparse_categorical_crossentropy: 0.0532 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0738\n",
      "Epoch 532/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1335 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0811 - val_loss: 0.1265 - val_sparse_categorical_crossentropy: 0.0458 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0806\n",
      "Epoch 533/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1230 - sparse_categorical_crossentropy: 0.0377 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0852 - val_loss: 0.1317 - val_sparse_categorical_crossentropy: 0.0578 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0740\n",
      "Epoch 534/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.1178 - sparse_categorical_crossentropy: 0.0400 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0778 - val_loss: 0.1149 - val_sparse_categorical_crossentropy: 0.0478 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0671\n",
      "Epoch 535/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1162 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0805 - val_loss: 0.1087 - val_sparse_categorical_crossentropy: 0.0518 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0569\n",
      "Epoch 536/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1169 - sparse_categorical_crossentropy: 0.0412 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0757 - val_loss: 0.1298 - val_sparse_categorical_crossentropy: 0.0631 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 537/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1228 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0831 - val_loss: 0.0993 - val_sparse_categorical_crossentropy: 0.0404 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0589\n",
      "Epoch 538/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1320 - sparse_categorical_crossentropy: 0.0481 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0840 - val_loss: 0.1289 - val_sparse_categorical_crossentropy: 0.0597 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0693\n",
      "Epoch 539/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1560 - sparse_categorical_crossentropy: 0.0633 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0927 - val_loss: 0.1077 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0668\n",
      "Epoch 540/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1208 - sparse_categorical_crossentropy: 0.0462 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0746 - val_loss: 0.1144 - val_sparse_categorical_crossentropy: 0.0567 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0577\n",
      "Epoch 541/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1200 - sparse_categorical_crossentropy: 0.0431 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0769 - val_loss: 0.1158 - val_sparse_categorical_crossentropy: 0.0468 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0690\n",
      "Epoch 542/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0320 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0817 - val_loss: 0.1093 - val_sparse_categorical_crossentropy: 0.0432 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0661\n",
      "Epoch 543/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1101 - sparse_categorical_crossentropy: 0.0322 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0779 - val_loss: 0.1045 - val_sparse_categorical_crossentropy: 0.0476 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0569\n",
      "Epoch 544/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1140 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0784 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0459 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0607\n",
      "Epoch 545/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1133 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0804 - val_loss: 0.1002 - val_sparse_categorical_crossentropy: 0.0387 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0614\n",
      "Epoch 546/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0339 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0802 - val_loss: 0.1136 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0645\n",
      "Epoch 547/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1074 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0738 - val_loss: 0.1141 - val_sparse_categorical_crossentropy: 0.0474 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0668\n",
      "Epoch 548/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.1194 - sparse_categorical_crossentropy: 0.0374 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0821 - val_loss: 0.1069 - val_sparse_categorical_crossentropy: 0.0564 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 549/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0794 - val_loss: 0.1115 - val_sparse_categorical_crossentropy: 0.0520 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0595\n",
      "Epoch 550/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1132 - sparse_categorical_crossentropy: 0.0354 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0778 - val_loss: 0.1216 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0782\n",
      "Epoch 551/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1127 - sparse_categorical_crossentropy: 0.0314 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0813 - val_loss: 0.1089 - val_sparse_categorical_crossentropy: 0.0499 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0590\n",
      "Epoch 552/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0364 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0756 - val_loss: 0.1362 - val_sparse_categorical_crossentropy: 0.0739 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0623\n",
      "Epoch 553/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1136 - sparse_categorical_crossentropy: 0.0337 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0799 - val_loss: 0.1180 - val_sparse_categorical_crossentropy: 0.0441 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0739\n",
      "Epoch 554/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1166 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0797 - val_loss: 0.1174 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0702\n",
      "Epoch 555/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1166 - sparse_categorical_crossentropy: 0.0385 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1074 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0629\n",
      "Epoch 556/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1273 - sparse_categorical_crossentropy: 0.0444 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1029 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 557/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1121 - sparse_categorical_crossentropy: 0.0298 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0823 - val_loss: 0.0988 - val_sparse_categorical_crossentropy: 0.0437 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 558/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.1071 - sparse_categorical_crossentropy: 0.0286 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0784 - val_loss: 0.0983 - val_sparse_categorical_crossentropy: 0.0501 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0482\n",
      "Epoch 559/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0371 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0764 - val_loss: 0.1066 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0600\n",
      "Epoch 560/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1108 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0784 - val_loss: 0.1417 - val_sparse_categorical_crossentropy: 0.0575 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0842\n",
      "Epoch 561/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1201 - sparse_categorical_crossentropy: 0.0420 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1108 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0684\n",
      "Epoch 562/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1266 - sparse_categorical_crossentropy: 0.0485 - sparse_categorical_accuracy: 0.9810 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1347 - val_sparse_categorical_crossentropy: 0.0619 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0728\n",
      "Epoch 563/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1116 - sparse_categorical_crossentropy: 0.0341 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0775 - val_loss: 0.1167 - val_sparse_categorical_crossentropy: 0.0573 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0594\n",
      "Epoch 564/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1433 - sparse_categorical_crossentropy: 0.0596 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0837 - val_loss: 0.1164 - val_sparse_categorical_crossentropy: 0.0465 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0699\n",
      "Epoch 565/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1326 - sparse_categorical_crossentropy: 0.0467 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1123 - val_sparse_categorical_crossentropy: 0.0436 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0687\n",
      "Epoch 566/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1545 - sparse_categorical_crossentropy: 0.0721 - sparse_categorical_accuracy: 0.9742 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1136 - val_sparse_categorical_crossentropy: 0.0470 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0666\n",
      "Epoch 567/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1541 - sparse_categorical_crossentropy: 0.0674 - sparse_categorical_accuracy: 0.9785 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1088 - val_sparse_categorical_crossentropy: 0.0483 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 568/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1274 - sparse_categorical_crossentropy: 0.0465 - sparse_categorical_accuracy: 0.9826 - scaled_adversarial_loss: 0.0810 - val_loss: 0.1081 - val_sparse_categorical_crossentropy: 0.0449 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0633\n",
      "Epoch 569/1000\n",
      "9/9 [==============================] - 3s 387ms/step - loss: 0.1345 - sparse_categorical_crossentropy: 0.0461 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0884 - val_loss: 0.1052 - val_sparse_categorical_crossentropy: 0.0460 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0592\n",
      "Epoch 570/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1341 - sparse_categorical_crossentropy: 0.0493 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0848 - val_loss: 0.1123 - val_sparse_categorical_crossentropy: 0.0534 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0589\n",
      "Epoch 571/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1338 - sparse_categorical_crossentropy: 0.0525 - sparse_categorical_accuracy: 0.9790 - scaled_adversarial_loss: 0.0813 - val_loss: 0.1095 - val_sparse_categorical_crossentropy: 0.0459 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0635\n",
      "Epoch 572/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1289 - sparse_categorical_crossentropy: 0.0421 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0867 - val_loss: 0.1081 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 573/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1162 - sparse_categorical_crossentropy: 0.0355 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0807 - val_loss: 0.1234 - val_sparse_categorical_crossentropy: 0.0487 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0747\n",
      "Epoch 574/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0314 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0735 - val_loss: 0.1261 - val_sparse_categorical_crossentropy: 0.0651 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0611\n",
      "Epoch 575/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1137 - sparse_categorical_crossentropy: 0.0405 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0731 - val_loss: 0.1169 - val_sparse_categorical_crossentropy: 0.0505 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 576/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0363 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1104 - val_sparse_categorical_crossentropy: 0.0449 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 577/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0296 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0845 - val_loss: 0.1192 - val_sparse_categorical_crossentropy: 0.0475 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0717\n",
      "Epoch 578/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1020 - sparse_categorical_crossentropy: 0.0277 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0743 - val_loss: 0.1118 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0577\n",
      "Epoch 579/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0294 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0755 - val_loss: 0.1031 - val_sparse_categorical_crossentropy: 0.0426 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 580/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1191 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0833 - val_loss: 0.1192 - val_sparse_categorical_crossentropy: 0.0502 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0690\n",
      "Epoch 581/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1212 - sparse_categorical_crossentropy: 0.0379 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0833 - val_loss: 0.1486 - val_sparse_categorical_crossentropy: 0.0630 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0856\n",
      "Epoch 582/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.1156 - sparse_categorical_crossentropy: 0.0353 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0803 - val_loss: 0.1094 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0643\n",
      "Epoch 583/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1098 - sparse_categorical_crossentropy: 0.0295 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0804 - val_loss: 0.1121 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0640\n",
      "Epoch 584/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0786 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 585/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1065 - sparse_categorical_crossentropy: 0.0341 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0724 - val_loss: 0.1235 - val_sparse_categorical_crossentropy: 0.0455 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0780\n",
      "Epoch 586/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1157 - sparse_categorical_crossentropy: 0.0373 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0783 - val_loss: 0.1114 - val_sparse_categorical_crossentropy: 0.0608 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 587/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1088 - sparse_categorical_crossentropy: 0.0308 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1228 - val_sparse_categorical_crossentropy: 0.0559 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0668\n",
      "Epoch 588/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1161 - sparse_categorical_crossentropy: 0.0357 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0804 - val_loss: 0.1118 - val_sparse_categorical_crossentropy: 0.0523 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0595\n",
      "Epoch 589/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1080 - sparse_categorical_crossentropy: 0.0340 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0740 - val_loss: 0.1215 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 590/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1199 - sparse_categorical_crossentropy: 0.0414 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0785 - val_loss: 0.1278 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 591/1000\n",
      "9/9 [==============================] - 3s 388ms/step - loss: 0.1131 - sparse_categorical_crossentropy: 0.0349 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0782 - val_loss: 0.1544 - val_sparse_categorical_crossentropy: 0.0616 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0928\n",
      "Epoch 592/1000\n",
      "9/9 [==============================] - 3s 381ms/step - loss: 0.1161 - sparse_categorical_crossentropy: 0.0360 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0800 - val_loss: 0.1262 - val_sparse_categorical_crossentropy: 0.0486 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0776\n",
      "Epoch 593/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1245 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0854 - val_loss: 0.1189 - val_sparse_categorical_crossentropy: 0.0535 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 594/1000\n",
      "9/9 [==============================] - 3s 379ms/step - loss: 0.1234 - sparse_categorical_crossentropy: 0.0371 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0863 - val_loss: 0.1130 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0681\n",
      "Epoch 595/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0403 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1299 - val_sparse_categorical_crossentropy: 0.0542 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0757\n",
      "Epoch 596/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0450 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0788 - val_loss: 0.1175 - val_sparse_categorical_crossentropy: 0.0469 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0707\n",
      "Epoch 597/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1232 - sparse_categorical_crossentropy: 0.0457 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0775 - val_loss: 0.1125 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0679\n",
      "Epoch 598/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0311 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1182 - val_sparse_categorical_crossentropy: 0.0562 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 599/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0497 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0785 - val_loss: 0.1171 - val_sparse_categorical_crossentropy: 0.0498 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0673\n",
      "Epoch 600/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1134 - sparse_categorical_crossentropy: 0.0380 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0754 - val_loss: 0.1159 - val_sparse_categorical_crossentropy: 0.0397 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0762\n",
      "Epoch 601/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1274 - sparse_categorical_crossentropy: 0.0444 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0829 - val_loss: 0.1157 - val_sparse_categorical_crossentropy: 0.0518 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0639\n",
      "Epoch 602/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1246 - sparse_categorical_crossentropy: 0.0442 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0804 - val_loss: 0.1143 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0681\n",
      "Epoch 603/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0410 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0796 - val_loss: 0.1126 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0615\n",
      "Epoch 604/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1248 - sparse_categorical_crossentropy: 0.0404 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0844 - val_loss: 0.1272 - val_sparse_categorical_crossentropy: 0.0403 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0868\n",
      "Epoch 605/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0818 - val_loss: 0.1146 - val_sparse_categorical_crossentropy: 0.0478 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0668\n",
      "Epoch 606/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1103 - sparse_categorical_crossentropy: 0.0347 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0756 - val_loss: 0.1048 - val_sparse_categorical_crossentropy: 0.0536 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 607/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1160 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0791 - val_loss: 0.0999 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0492\n",
      "Epoch 608/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1301 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0777 - val_loss: 0.1090 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0684\n",
      "Epoch 609/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1369 - sparse_categorical_crossentropy: 0.0451 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0918 - val_loss: 0.1244 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0718\n",
      "Epoch 610/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1282 - sparse_categorical_crossentropy: 0.0443 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0839 - val_loss: 0.1272 - val_sparse_categorical_crossentropy: 0.0615 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0656\n",
      "Epoch 611/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0400 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0790 - val_loss: 0.1355 - val_sparse_categorical_crossentropy: 0.0667 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 612/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1336 - sparse_categorical_crossentropy: 0.0466 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0870 - val_loss: 0.1264 - val_sparse_categorical_crossentropy: 0.0653 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0611\n",
      "Epoch 613/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0377 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0830 - val_loss: 0.1227 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0781\n",
      "Epoch 614/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1389 - sparse_categorical_crossentropy: 0.0516 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0873 - val_loss: 0.1156 - val_sparse_categorical_crossentropy: 0.0488 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0669\n",
      "Epoch 615/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1553 - sparse_categorical_crossentropy: 0.0714 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0839 - val_loss: 0.1118 - val_sparse_categorical_crossentropy: 0.0489 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0630\n",
      "Epoch 616/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1595 - sparse_categorical_crossentropy: 0.0720 - sparse_categorical_accuracy: 0.9761 - scaled_adversarial_loss: 0.0875 - val_loss: 0.1583 - val_sparse_categorical_crossentropy: 0.0803 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0781\n",
      "Epoch 617/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1392 - sparse_categorical_crossentropy: 0.0507 - sparse_categorical_accuracy: 0.9817 - scaled_adversarial_loss: 0.0886 - val_loss: 0.1289 - val_sparse_categorical_crossentropy: 0.0553 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0736\n",
      "Epoch 618/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1430 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9824 - scaled_adversarial_loss: 0.0871 - val_loss: 0.1174 - val_sparse_categorical_crossentropy: 0.0512 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0662\n",
      "Epoch 619/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1203 - sparse_categorical_crossentropy: 0.0359 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0844 - val_loss: 0.1116 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0674\n",
      "Epoch 620/1000\n",
      "9/9 [==============================] - 3s 374ms/step - loss: 0.1188 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0793 - val_loss: 0.1405 - val_sparse_categorical_crossentropy: 0.0566 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0840\n",
      "Epoch 621/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1227 - sparse_categorical_crossentropy: 0.0400 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0826 - val_loss: 0.1415 - val_sparse_categorical_crossentropy: 0.0584 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0830\n",
      "Epoch 622/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1177 - sparse_categorical_crossentropy: 0.0382 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0795 - val_loss: 0.1200 - val_sparse_categorical_crossentropy: 0.0525 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0675\n",
      "Epoch 623/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1238 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0847 - val_loss: 0.1048 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0607\n",
      "Epoch 624/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1180 - sparse_categorical_crossentropy: 0.0360 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0819 - val_loss: 0.1234 - val_sparse_categorical_crossentropy: 0.0532 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0702\n",
      "Epoch 625/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1148 - sparse_categorical_crossentropy: 0.0296 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0852 - val_loss: 0.1052 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0634\n",
      "Epoch 626/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0411 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0779 - val_loss: 0.1312 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0802\n",
      "Epoch 627/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.1226 - sparse_categorical_crossentropy: 0.0438 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0788 - val_loss: 0.1141 - val_sparse_categorical_crossentropy: 0.0605 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0535\n",
      "Epoch 628/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1222 - sparse_categorical_crossentropy: 0.0382 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0840 - val_loss: 0.1030 - val_sparse_categorical_crossentropy: 0.0418 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0611\n",
      "Epoch 629/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1341 - sparse_categorical_crossentropy: 0.0472 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0869 - val_loss: 0.1040 - val_sparse_categorical_crossentropy: 0.0534 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 630/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1426 - sparse_categorical_crossentropy: 0.0621 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0805 - val_loss: 0.1278 - val_sparse_categorical_crossentropy: 0.0505 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0773\n",
      "Epoch 631/1000\n",
      "9/9 [==============================] - 3s 321ms/step - loss: 0.1322 - sparse_categorical_crossentropy: 0.0479 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0843 - val_loss: 0.1192 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0708\n",
      "Epoch 632/1000\n",
      "9/9 [==============================] - 3s 317ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0382 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1018 - val_sparse_categorical_crossentropy: 0.0494 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 633/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1221 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0804 - val_loss: 0.1248 - val_sparse_categorical_crossentropy: 0.0581 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 634/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1257 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0821 - val_loss: 0.1137 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0622\n",
      "Epoch 635/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1299 - sparse_categorical_crossentropy: 0.0437 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0862 - val_loss: 0.1082 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 636/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1249 - sparse_categorical_crossentropy: 0.0418 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0831 - val_loss: 0.1107 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0599\n",
      "Epoch 637/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1224 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0836 - val_loss: 0.1020 - val_sparse_categorical_crossentropy: 0.0498 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 638/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0317 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0830 - val_loss: 0.1052 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 639/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1112 - sparse_categorical_crossentropy: 0.0336 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0776 - val_loss: 0.1077 - val_sparse_categorical_crossentropy: 0.0457 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 640/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1114 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1029 - val_sparse_categorical_crossentropy: 0.0468 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0561\n",
      "Epoch 641/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1130 - sparse_categorical_crossentropy: 0.0341 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0789 - val_loss: 0.1011 - val_sparse_categorical_crossentropy: 0.0405 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 642/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1052 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0776 - val_loss: 0.1113 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0602\n",
      "Epoch 643/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1038 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0760 - val_loss: 0.1072 - val_sparse_categorical_crossentropy: 0.0499 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0573\n",
      "Epoch 644/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1192 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0815 - val_loss: 0.1150 - val_sparse_categorical_crossentropy: 0.0510 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0639\n",
      "Epoch 645/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.1157 - sparse_categorical_crossentropy: 0.0380 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0778 - val_loss: 0.1098 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 646/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0806 - val_loss: 0.0997 - val_sparse_categorical_crossentropy: 0.0476 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0521\n",
      "Epoch 647/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1093 - sparse_categorical_crossentropy: 0.0341 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0978 - val_sparse_categorical_crossentropy: 0.0483 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0495\n",
      "Epoch 648/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0771 - val_loss: 0.1035 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0610\n",
      "Epoch 649/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0300 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0820 - val_loss: 0.1003 - val_sparse_categorical_crossentropy: 0.0397 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 650/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1038 - sparse_categorical_crossentropy: 0.0289 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0748 - val_loss: 0.1063 - val_sparse_categorical_crossentropy: 0.0454 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0609\n",
      "Epoch 651/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.1153 - sparse_categorical_crossentropy: 0.0381 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0773 - val_loss: 0.1027 - val_sparse_categorical_crossentropy: 0.0482 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 652/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1187 - sparse_categorical_crossentropy: 0.0430 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0758 - val_loss: 0.1101 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 653/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1044 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1111 - val_sparse_categorical_crossentropy: 0.0504 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0607\n",
      "Epoch 654/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0336 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0812 - val_loss: 0.1240 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0773\n",
      "Epoch 655/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1187 - sparse_categorical_crossentropy: 0.0396 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0791 - val_loss: 0.0979 - val_sparse_categorical_crossentropy: 0.0495 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0484\n",
      "Epoch 656/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1157 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0813 - val_loss: 0.0988 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0507\n",
      "Epoch 657/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1167 - sparse_categorical_crossentropy: 0.0359 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0808 - val_loss: 0.1083 - val_sparse_categorical_crossentropy: 0.0494 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0589\n",
      "Epoch 658/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1122 - sparse_categorical_crossentropy: 0.0352 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0770 - val_loss: 0.1104 - val_sparse_categorical_crossentropy: 0.0534 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 659/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0330 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0790 - val_loss: 0.1254 - val_sparse_categorical_crossentropy: 0.0590 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 660/1000\n",
      "9/9 [==============================] - 3s 321ms/step - loss: 0.1307 - sparse_categorical_crossentropy: 0.0528 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0779 - val_loss: 0.1012 - val_sparse_categorical_crossentropy: 0.0474 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0538\n",
      "Epoch 661/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1175 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0777 - val_loss: 0.1107 - val_sparse_categorical_crossentropy: 0.0455 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0652\n",
      "Epoch 662/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1178 - sparse_categorical_crossentropy: 0.0412 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1080 - val_sparse_categorical_crossentropy: 0.0562 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0518\n",
      "Epoch 663/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1143 - sparse_categorical_crossentropy: 0.0365 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0778 - val_loss: 0.1104 - val_sparse_categorical_crossentropy: 0.0532 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0572\n",
      "Epoch 664/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1162 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0774 - val_loss: 0.1099 - val_sparse_categorical_crossentropy: 0.0518 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0581\n",
      "Epoch 665/1000\n",
      "9/9 [==============================] - 3s 321ms/step - loss: 0.1087 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0785 - val_loss: 0.0949 - val_sparse_categorical_crossentropy: 0.0415 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 666/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1144 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0800 - val_loss: 0.1211 - val_sparse_categorical_crossentropy: 0.0520 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0692\n",
      "Epoch 667/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1060 - sparse_categorical_crossentropy: 0.0257 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0803 - val_loss: 0.1003 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 668/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1040 - sparse_categorical_crossentropy: 0.0289 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0751 - val_loss: 0.1076 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0610\n",
      "Epoch 669/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1065 - sparse_categorical_crossentropy: 0.0317 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0747 - val_loss: 0.1083 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0602\n",
      "Epoch 670/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1155 - sparse_categorical_crossentropy: 0.0372 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0784 - val_loss: 0.1113 - val_sparse_categorical_crossentropy: 0.0549 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 671/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1156 - sparse_categorical_crossentropy: 0.0339 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0817 - val_loss: 0.0969 - val_sparse_categorical_crossentropy: 0.0439 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0529\n",
      "Epoch 672/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1066 - sparse_categorical_crossentropy: 0.0310 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0756 - val_loss: 0.1075 - val_sparse_categorical_crossentropy: 0.0404 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0670\n",
      "Epoch 673/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1026 - sparse_categorical_crossentropy: 0.0271 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0754 - val_loss: 0.1300 - val_sparse_categorical_crossentropy: 0.0745 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 674/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1106 - sparse_categorical_crossentropy: 0.0355 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0981 - val_sparse_categorical_crossentropy: 0.0411 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 675/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1207 - sparse_categorical_crossentropy: 0.0448 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0760 - val_loss: 0.1104 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0604\n",
      "Epoch 676/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1199 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9846 - scaled_adversarial_loss: 0.0808 - val_loss: 0.1110 - val_sparse_categorical_crossentropy: 0.0504 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0606\n",
      "Epoch 677/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1122 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0771 - val_loss: 0.1212 - val_sparse_categorical_crossentropy: 0.0456 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 678/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1227 - sparse_categorical_crossentropy: 0.0410 - sparse_categorical_accuracy: 0.9870 - scaled_adversarial_loss: 0.0817 - val_loss: 0.1161 - val_sparse_categorical_crossentropy: 0.0530 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0631\n",
      "Epoch 679/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1029 - sparse_categorical_crossentropy: 0.0270 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0759 - val_loss: 0.1059 - val_sparse_categorical_crossentropy: 0.0374 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0685\n",
      "Epoch 680/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1159 - sparse_categorical_crossentropy: 0.0350 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0808 - val_loss: 0.1101 - val_sparse_categorical_crossentropy: 0.0529 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0572\n",
      "Epoch 681/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1138 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0747 - val_loss: 0.1002 - val_sparse_categorical_crossentropy: 0.0437 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0566\n",
      "Epoch 682/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1148 - sparse_categorical_crossentropy: 0.0406 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0742 - val_loss: 0.1074 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0649\n",
      "Epoch 683/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0770 - val_loss: 0.1011 - val_sparse_categorical_crossentropy: 0.0460 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 684/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1020 - sparse_categorical_crossentropy: 0.0269 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0751 - val_loss: 0.0901 - val_sparse_categorical_crossentropy: 0.0417 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0484\n",
      "Epoch 685/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1069 - sparse_categorical_crossentropy: 0.0287 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0782 - val_loss: 0.0876 - val_sparse_categorical_crossentropy: 0.0369 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0508\n",
      "Epoch 686/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1100 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0940 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0515\n",
      "Epoch 687/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1027 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0689 - val_loss: 0.1190 - val_sparse_categorical_crossentropy: 0.0631 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0559\n",
      "Epoch 688/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1159 - sparse_categorical_crossentropy: 0.0378 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1037 - val_sparse_categorical_crossentropy: 0.0415 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0621\n",
      "Epoch 689/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.1072 - sparse_categorical_crossentropy: 0.0311 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0761 - val_loss: 0.1073 - val_sparse_categorical_crossentropy: 0.0492 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0581\n",
      "Epoch 690/1000\n",
      "9/9 [==============================] - 3s 395ms/step - loss: 0.1044 - sparse_categorical_crossentropy: 0.0272 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0772 - val_loss: 0.1112 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0628\n",
      "Epoch 691/1000\n",
      "9/9 [==============================] - 4s 397ms/step - loss: 0.1050 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0746 - val_loss: 0.0965 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0559\n",
      "Epoch 692/1000\n",
      "9/9 [==============================] - 3s 388ms/step - loss: 0.1062 - sparse_categorical_crossentropy: 0.0284 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0777 - val_loss: 0.1092 - val_sparse_categorical_crossentropy: 0.0561 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0530\n",
      "Epoch 693/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1140 - sparse_categorical_crossentropy: 0.0403 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0737 - val_loss: 0.1017 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0579\n",
      "Epoch 694/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0751 - val_loss: 0.1120 - val_sparse_categorical_crossentropy: 0.0538 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0582\n",
      "Epoch 695/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0361 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0822 - val_loss: 0.1241 - val_sparse_categorical_crossentropy: 0.0465 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0775\n",
      "Epoch 696/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1162 - sparse_categorical_crossentropy: 0.0350 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0812 - val_loss: 0.1146 - val_sparse_categorical_crossentropy: 0.0534 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0611\n",
      "Epoch 697/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.1047 - sparse_categorical_crossentropy: 0.0279 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0945 - val_sparse_categorical_crossentropy: 0.0360 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 698/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1118 - sparse_categorical_crossentropy: 0.0341 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0778 - val_loss: 0.1054 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0634\n",
      "Epoch 699/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.1255 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0859 - val_loss: 0.1157 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0711\n",
      "Epoch 700/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1136 - sparse_categorical_crossentropy: 0.0408 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0728 - val_loss: 0.1038 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0541\n",
      "Epoch 701/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1311 - sparse_categorical_crossentropy: 0.0586 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0725 - val_loss: 0.1308 - val_sparse_categorical_crossentropy: 0.0620 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0688\n",
      "Epoch 702/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1127 - sparse_categorical_crossentropy: 0.0384 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0743 - val_loss: 0.1122 - val_sparse_categorical_crossentropy: 0.0468 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 703/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1187 - sparse_categorical_crossentropy: 0.0363 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1229 - val_sparse_categorical_crossentropy: 0.0416 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0813\n",
      "Epoch 704/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1040 - sparse_categorical_crossentropy: 0.0306 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0864 - val_sparse_categorical_crossentropy: 0.0377 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0487\n",
      "Epoch 705/1000\n",
      "9/9 [==============================] - 3s 338ms/step - loss: 0.0976 - sparse_categorical_crossentropy: 0.0234 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0742 - val_loss: 0.1111 - val_sparse_categorical_crossentropy: 0.0444 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 706/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1156 - sparse_categorical_crossentropy: 0.0389 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0982 - val_sparse_categorical_crossentropy: 0.0401 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0581\n",
      "Epoch 707/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1081 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0664 - val_loss: 0.1098 - val_sparse_categorical_crossentropy: 0.0584 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 708/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1357 - sparse_categorical_crossentropy: 0.0560 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0797 - val_loss: 0.1143 - val_sparse_categorical_crossentropy: 0.0536 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0607\n",
      "Epoch 709/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.1330 - sparse_categorical_crossentropy: 0.0565 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1206 - val_sparse_categorical_crossentropy: 0.0603 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0603\n",
      "Epoch 710/1000\n",
      "9/9 [==============================] - 3s 318ms/step - loss: 0.1215 - sparse_categorical_crossentropy: 0.0381 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0834 - val_loss: 0.1029 - val_sparse_categorical_crossentropy: 0.0405 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0624\n",
      "Epoch 711/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1087 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0755 - val_loss: 0.1385 - val_sparse_categorical_crossentropy: 0.0711 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0673\n",
      "Epoch 712/1000\n",
      "9/9 [==============================] - 3s 324ms/step - loss: 0.1041 - sparse_categorical_crossentropy: 0.0287 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0754 - val_loss: 0.1054 - val_sparse_categorical_crossentropy: 0.0556 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0498\n",
      "Epoch 713/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1067 - sparse_categorical_crossentropy: 0.0318 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0749 - val_loss: 0.1077 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0563\n",
      "Epoch 714/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0372 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0763 - val_loss: 0.1010 - val_sparse_categorical_crossentropy: 0.0416 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0594\n",
      "Epoch 715/1000\n",
      "9/9 [==============================] - 3s 319ms/step - loss: 0.1015 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0681 - val_loss: 0.0972 - val_sparse_categorical_crossentropy: 0.0389 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0582\n",
      "Epoch 716/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1134 - sparse_categorical_crossentropy: 0.0316 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0818 - val_loss: 0.1053 - val_sparse_categorical_crossentropy: 0.0482 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0571\n",
      "Epoch 717/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1101 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0799 - val_loss: 0.0912 - val_sparse_categorical_crossentropy: 0.0396 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 718/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1155 - sparse_categorical_crossentropy: 0.0386 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0769 - val_loss: 0.0999 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0554\n",
      "Epoch 719/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1192 - sparse_categorical_crossentropy: 0.0444 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0748 - val_loss: 0.1117 - val_sparse_categorical_crossentropy: 0.0564 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 720/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0326 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0793 - val_loss: 0.1050 - val_sparse_categorical_crossentropy: 0.0435 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0615\n",
      "Epoch 721/1000\n",
      "9/9 [==============================] - 3s 318ms/step - loss: 0.1123 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0790 - val_loss: 0.1070 - val_sparse_categorical_crossentropy: 0.0564 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0506\n",
      "Epoch 722/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.1028 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0919 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0517\n",
      "Epoch 723/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0706 - val_loss: 0.1075 - val_sparse_categorical_crossentropy: 0.0542 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 724/1000\n",
      "9/9 [==============================] - 3s 321ms/step - loss: 0.1090 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0758 - val_loss: 0.0886 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0481\n",
      "Epoch 725/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1126 - sparse_categorical_crossentropy: 0.0369 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0757 - val_loss: 0.1209 - val_sparse_categorical_crossentropy: 0.0534 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0675\n",
      "Epoch 726/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1323 - sparse_categorical_crossentropy: 0.0494 - sparse_categorical_accuracy: 0.9836 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1160 - val_sparse_categorical_crossentropy: 0.0508 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0653\n",
      "Epoch 727/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0382 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1086 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0571\n",
      "Epoch 728/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1125 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0755 - val_loss: 0.1214 - val_sparse_categorical_crossentropy: 0.0475 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0739\n",
      "Epoch 729/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1117 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0788 - val_loss: 0.1029 - val_sparse_categorical_crossentropy: 0.0505 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 730/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1166 - sparse_categorical_crossentropy: 0.0391 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0775 - val_loss: 0.1143 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0671\n",
      "Epoch 731/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1354 - sparse_categorical_crossentropy: 0.0555 - sparse_categorical_accuracy: 0.9802 - scaled_adversarial_loss: 0.0799 - val_loss: 0.1107 - val_sparse_categorical_crossentropy: 0.0459 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0648\n",
      "Epoch 732/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1244 - sparse_categorical_crossentropy: 0.0455 - sparse_categorical_accuracy: 0.9831 - scaled_adversarial_loss: 0.0789 - val_loss: 0.1145 - val_sparse_categorical_crossentropy: 0.0583 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0562\n",
      "Epoch 733/1000\n",
      "9/9 [==============================] - 4s 392ms/step - loss: 0.1300 - sparse_categorical_crossentropy: 0.0467 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0833 - val_loss: 0.1012 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0509\n",
      "Epoch 734/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1086 - sparse_categorical_crossentropy: 0.0320 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0476\n",
      "Epoch 735/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1047 - sparse_categorical_crossentropy: 0.0328 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0719 - val_loss: 0.1238 - val_sparse_categorical_crossentropy: 0.0554 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 736/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1119 - sparse_categorical_crossentropy: 0.0359 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0761 - val_loss: 0.0959 - val_sparse_categorical_crossentropy: 0.0404 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0555\n",
      "Epoch 737/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1190 - sparse_categorical_crossentropy: 0.0386 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0804 - val_loss: 0.1215 - val_sparse_categorical_crossentropy: 0.0429 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0786\n",
      "Epoch 738/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.1164 - sparse_categorical_crossentropy: 0.0313 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0851 - val_loss: 0.1096 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0623\n",
      "Epoch 739/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1075 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0743 - val_loss: 0.1343 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0840\n",
      "Epoch 740/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1059 - sparse_categorical_crossentropy: 0.0299 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0760 - val_loss: 0.1277 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0857\n",
      "Epoch 741/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.1102 - sparse_categorical_crossentropy: 0.0309 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0793 - val_loss: 0.1000 - val_sparse_categorical_crossentropy: 0.0457 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 742/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1089 - sparse_categorical_crossentropy: 0.0280 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0808 - val_loss: 0.0954 - val_sparse_categorical_crossentropy: 0.0384 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 743/1000\n",
      "9/9 [==============================] - 3s 381ms/step - loss: 0.1089 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0815 - val_loss: 0.1068 - val_sparse_categorical_crossentropy: 0.0412 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0656\n",
      "Epoch 744/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.0991 - sparse_categorical_crossentropy: 0.0235 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0756 - val_loss: 0.0933 - val_sparse_categorical_crossentropy: 0.0479 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0453\n",
      "Epoch 745/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1058 - sparse_categorical_crossentropy: 0.0319 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0739 - val_loss: 0.1079 - val_sparse_categorical_crossentropy: 0.0512 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0567\n",
      "Epoch 746/1000\n",
      "9/9 [==============================] - 4s 396ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0317 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0788 - val_loss: 0.0961 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 747/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.1176 - sparse_categorical_crossentropy: 0.0360 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0816 - val_loss: 0.0967 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0561\n",
      "Epoch 748/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1112 - sparse_categorical_crossentropy: 0.0344 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0768 - val_loss: 0.0986 - val_sparse_categorical_crossentropy: 0.0441 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0545\n",
      "Epoch 749/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1142 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0733 - val_loss: 0.1077 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 750/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1081 - sparse_categorical_crossentropy: 0.0345 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0737 - val_loss: 0.0977 - val_sparse_categorical_crossentropy: 0.0376 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 751/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0416 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0704 - val_loss: 0.1321 - val_sparse_categorical_crossentropy: 0.0513 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0808\n",
      "Epoch 752/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1041 - sparse_categorical_crossentropy: 0.0255 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0786 - val_loss: 0.1139 - val_sparse_categorical_crossentropy: 0.0414 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0725\n",
      "Epoch 753/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1114 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0781 - val_loss: 0.1215 - val_sparse_categorical_crossentropy: 0.0440 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0775\n",
      "Epoch 754/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.1040 - sparse_categorical_crossentropy: 0.0324 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0716 - val_loss: 0.1142 - val_sparse_categorical_crossentropy: 0.0443 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0700\n",
      "Epoch 755/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1131 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0793 - val_loss: 0.1005 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0557\n",
      "Epoch 756/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1072 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0729 - val_loss: 0.0972 - val_sparse_categorical_crossentropy: 0.0371 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 757/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1216 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0848 - val_loss: 0.1038 - val_sparse_categorical_crossentropy: 0.0463 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0575\n",
      "Epoch 758/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0316 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0779 - val_loss: 0.1149 - val_sparse_categorical_crossentropy: 0.0387 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0762\n",
      "Epoch 759/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.1050 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0748 - val_loss: 0.1056 - val_sparse_categorical_crossentropy: 0.0439 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0617\n",
      "Epoch 760/1000\n",
      "9/9 [==============================] - 3s 394ms/step - loss: 0.1002 - sparse_categorical_crossentropy: 0.0236 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1071 - val_sparse_categorical_crossentropy: 0.0408 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0663\n",
      "Epoch 761/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0348 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0729 - val_loss: 0.1016 - val_sparse_categorical_crossentropy: 0.0422 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0594\n",
      "Epoch 762/1000\n",
      "9/9 [==============================] - 3s 355ms/step - loss: 0.1139 - sparse_categorical_crossentropy: 0.0310 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0829 - val_loss: 0.1077 - val_sparse_categorical_crossentropy: 0.0506 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0570\n",
      "Epoch 763/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1035 - sparse_categorical_crossentropy: 0.0263 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0772 - val_loss: 0.1022 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0525\n",
      "Epoch 764/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.0983 - sparse_categorical_crossentropy: 0.0290 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0693 - val_loss: 0.1018 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0589\n",
      "Epoch 765/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1041 - sparse_categorical_crossentropy: 0.0301 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0740 - val_loss: 0.1263 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0778\n",
      "Epoch 766/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.0977 - sparse_categorical_crossentropy: 0.0219 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0758 - val_loss: 0.1177 - val_sparse_categorical_crossentropy: 0.0380 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0797\n",
      "Epoch 767/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.0925 - sparse_categorical_crossentropy: 0.0247 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0678 - val_loss: 0.1051 - val_sparse_categorical_crossentropy: 0.0446 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0605\n",
      "Epoch 768/1000\n",
      "9/9 [==============================] - 3s 319ms/step - loss: 0.1022 - sparse_categorical_crossentropy: 0.0287 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0735 - val_loss: 0.1084 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0599\n",
      "Epoch 769/1000\n",
      "9/9 [==============================] - 3s 319ms/step - loss: 0.0963 - sparse_categorical_crossentropy: 0.0220 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0742 - val_loss: 0.0976 - val_sparse_categorical_crossentropy: 0.0414 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0562\n",
      "Epoch 770/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.0909 - sparse_categorical_crossentropy: 0.0220 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0689 - val_loss: 0.1002 - val_sparse_categorical_crossentropy: 0.0349 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0653\n",
      "Epoch 771/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.0945 - sparse_categorical_crossentropy: 0.0259 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0687 - val_loss: 0.0952 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 772/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.0945 - sparse_categorical_crossentropy: 0.0240 - sparse_categorical_accuracy: 0.9942 - scaled_adversarial_loss: 0.0705 - val_loss: 0.0895 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 773/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.0940 - sparse_categorical_crossentropy: 0.0247 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0693 - val_loss: 0.1041 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0593\n",
      "Epoch 774/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.0998 - sparse_categorical_crossentropy: 0.0291 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0990 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 775/1000\n",
      "9/9 [==============================] - 3s 321ms/step - loss: 0.0993 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0691 - val_loss: 0.1278 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0817\n",
      "Epoch 776/1000\n",
      "9/9 [==============================] - 3s 321ms/step - loss: 0.1005 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0730 - val_loss: 0.1135 - val_sparse_categorical_crossentropy: 0.0479 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0655\n",
      "Epoch 777/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1000 - sparse_categorical_crossentropy: 0.0270 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0731 - val_loss: 0.1070 - val_sparse_categorical_crossentropy: 0.0418 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0652\n",
      "Epoch 778/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1004 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0737 - val_loss: 0.1295 - val_sparse_categorical_crossentropy: 0.0530 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0765\n",
      "Epoch 779/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1017 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0696 - val_loss: 0.1108 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0602\n",
      "Epoch 780/1000\n",
      "9/9 [==============================] - 3s 399ms/step - loss: 0.1136 - sparse_categorical_crossentropy: 0.0364 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0771 - val_loss: 0.1120 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0617\n",
      "Epoch 781/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1239 - sparse_categorical_crossentropy: 0.0443 - sparse_categorical_accuracy: 0.9814 - scaled_adversarial_loss: 0.0796 - val_loss: 0.1066 - val_sparse_categorical_crossentropy: 0.0392 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0674\n",
      "Epoch 782/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0533 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0773 - val_loss: 0.1147 - val_sparse_categorical_crossentropy: 0.0510 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0637\n",
      "Epoch 783/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1304 - sparse_categorical_crossentropy: 0.0469 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0835 - val_loss: 0.1255 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0756\n",
      "Epoch 784/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.1327 - sparse_categorical_crossentropy: 0.0502 - sparse_categorical_accuracy: 0.9831 - scaled_adversarial_loss: 0.0825 - val_loss: 0.1091 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0644\n",
      "Epoch 785/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1231 - sparse_categorical_crossentropy: 0.0463 - sparse_categorical_accuracy: 0.9819 - scaled_adversarial_loss: 0.0769 - val_loss: 0.1173 - val_sparse_categorical_crossentropy: 0.0449 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0723\n",
      "Epoch 786/1000\n",
      "9/9 [==============================] - 3s 382ms/step - loss: 0.1217 - sparse_categorical_crossentropy: 0.0443 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0773 - val_loss: 0.1047 - val_sparse_categorical_crossentropy: 0.0382 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0665\n",
      "Epoch 787/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1066 - sparse_categorical_crossentropy: 0.0320 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0746 - val_loss: 0.1113 - val_sparse_categorical_crossentropy: 0.0492 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0621\n",
      "Epoch 788/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1098 - sparse_categorical_crossentropy: 0.0312 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0786 - val_loss: 0.1061 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0696\n",
      "Epoch 789/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.0985 - sparse_categorical_crossentropy: 0.0277 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0708 - val_loss: 0.1132 - val_sparse_categorical_crossentropy: 0.0442 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0690\n",
      "Epoch 790/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1062 - sparse_categorical_crossentropy: 0.0318 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0744 - val_loss: 0.1146 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0619\n",
      "Epoch 791/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1037 - sparse_categorical_crossentropy: 0.0279 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0758 - val_loss: 0.1176 - val_sparse_categorical_crossentropy: 0.0355 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0821\n",
      "Epoch 792/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1039 - sparse_categorical_crossentropy: 0.0318 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0721 - val_loss: 0.1052 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0690\n",
      "Epoch 793/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1002 - sparse_categorical_crossentropy: 0.0272 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0730 - val_loss: 0.0910 - val_sparse_categorical_crossentropy: 0.0354 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 794/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1025 - sparse_categorical_crossentropy: 0.0280 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0745 - val_loss: 0.1098 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0674\n",
      "Epoch 795/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0790 - val_loss: 0.1032 - val_sparse_categorical_crossentropy: 0.0481 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 796/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.1179 - sparse_categorical_crossentropy: 0.0408 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0771 - val_loss: 0.1276 - val_sparse_categorical_crossentropy: 0.0422 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0854\n",
      "Epoch 797/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1145 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0823 - val_loss: 0.0941 - val_sparse_categorical_crossentropy: 0.0401 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0540\n",
      "Epoch 798/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1037 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0757 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0617\n",
      "Epoch 799/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0809 - val_loss: 0.1186 - val_sparse_categorical_crossentropy: 0.0482 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 800/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1040 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0760 - val_loss: 0.1349 - val_sparse_categorical_crossentropy: 0.0509 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0840\n",
      "Epoch 801/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0301 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0750 - val_loss: 0.1079 - val_sparse_categorical_crossentropy: 0.0430 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0649\n",
      "Epoch 802/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.0994 - sparse_categorical_crossentropy: 0.0301 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0693 - val_loss: 0.1316 - val_sparse_categorical_crossentropy: 0.0673 - val_sparse_categorical_accuracy: 0.9740 - val_scaled_adversarial_loss: 0.0643\n",
      "Epoch 803/1000\n",
      "9/9 [==============================] - 3s 383ms/step - loss: 0.1203 - sparse_categorical_crossentropy: 0.0386 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0816 - val_loss: 0.1013 - val_sparse_categorical_crossentropy: 0.0477 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0535\n",
      "Epoch 804/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0330 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0748 - val_loss: 0.1264 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0779\n",
      "Epoch 805/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1305 - sparse_categorical_crossentropy: 0.0492 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0814 - val_loss: 0.1135 - val_sparse_categorical_crossentropy: 0.0429 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0706\n",
      "Epoch 806/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1294 - sparse_categorical_crossentropy: 0.0501 - sparse_categorical_accuracy: 0.9829 - scaled_adversarial_loss: 0.0793 - val_loss: 0.1494 - val_sparse_categorical_crossentropy: 0.0734 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0760\n",
      "Epoch 807/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1219 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0791 - val_loss: 0.1031 - val_sparse_categorical_crossentropy: 0.0471 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0560\n",
      "Epoch 808/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.1099 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1104 - val_sparse_categorical_crossentropy: 0.0588 - val_sparse_categorical_accuracy: 0.9769 - val_scaled_adversarial_loss: 0.0516\n",
      "Epoch 809/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1165 - sparse_categorical_crossentropy: 0.0420 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0745 - val_loss: 0.1134 - val_sparse_categorical_crossentropy: 0.0441 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0692\n",
      "Epoch 810/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1150 - sparse_categorical_crossentropy: 0.0352 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0799 - val_loss: 0.1039 - val_sparse_categorical_crossentropy: 0.0407 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0632\n",
      "Epoch 811/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1021 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0687 - val_loss: 0.1107 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0662\n",
      "Epoch 812/1000\n",
      "9/9 [==============================] - 3s 366ms/step - loss: 0.1036 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0755 - val_loss: 0.1140 - val_sparse_categorical_crossentropy: 0.0457 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 813/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1029 - sparse_categorical_crossentropy: 0.0275 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0753 - val_loss: 0.1078 - val_sparse_categorical_crossentropy: 0.0527 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 814/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.0916 - sparse_categorical_crossentropy: 0.0207 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0709 - val_loss: 0.0948 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 815/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.1099 - sparse_categorical_crossentropy: 0.0313 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0786 - val_loss: 0.1192 - val_sparse_categorical_crossentropy: 0.0668 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0525\n",
      "Epoch 816/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1082 - sparse_categorical_crossentropy: 0.0340 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0742 - val_loss: 0.1323 - val_sparse_categorical_crossentropy: 0.0580 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0743\n",
      "Epoch 817/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1872 - sparse_categorical_crossentropy: 0.1067 - sparse_categorical_accuracy: 0.9578 - scaled_adversarial_loss: 0.0806 - val_loss: 0.1088 - val_sparse_categorical_crossentropy: 0.0465 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0623\n",
      "Epoch 818/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1427 - sparse_categorical_crossentropy: 0.0625 - sparse_categorical_accuracy: 0.9769 - scaled_adversarial_loss: 0.0802 - val_loss: 0.1034 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0550\n",
      "Epoch 819/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1337 - sparse_categorical_crossentropy: 0.0523 - sparse_categorical_accuracy: 0.9814 - scaled_adversarial_loss: 0.0814 - val_loss: 0.1203 - val_sparse_categorical_crossentropy: 0.0618 - val_sparse_categorical_accuracy: 0.9750 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 820/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1317 - sparse_categorical_crossentropy: 0.0510 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0806 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0514 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0553\n",
      "Epoch 821/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1445 - sparse_categorical_crossentropy: 0.0649 - sparse_categorical_accuracy: 0.9783 - scaled_adversarial_loss: 0.0796 - val_loss: 0.0943 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0495\n",
      "Epoch 822/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1182 - sparse_categorical_crossentropy: 0.0414 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0768 - val_loss: 0.1234 - val_sparse_categorical_crossentropy: 0.0530 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0704\n",
      "Epoch 823/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1304 - sparse_categorical_crossentropy: 0.0463 - sparse_categorical_accuracy: 0.9853 - scaled_adversarial_loss: 0.0841 - val_loss: 0.1170 - val_sparse_categorical_crossentropy: 0.0494 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0676\n",
      "Epoch 824/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1093 - sparse_categorical_crossentropy: 0.0293 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0800 - val_loss: 0.1194 - val_sparse_categorical_crossentropy: 0.0723 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0471\n",
      "Epoch 825/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1258 - sparse_categorical_crossentropy: 0.0473 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0784 - val_loss: 0.1036 - val_sparse_categorical_crossentropy: 0.0462 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0574\n",
      "Epoch 826/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1429 - sparse_categorical_crossentropy: 0.0605 - sparse_categorical_accuracy: 0.9822 - scaled_adversarial_loss: 0.0824 - val_loss: 0.0985 - val_sparse_categorical_crossentropy: 0.0400 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 827/1000\n",
      "9/9 [==============================] - 3s 367ms/step - loss: 0.1323 - sparse_categorical_crossentropy: 0.0522 - sparse_categorical_accuracy: 0.9848 - scaled_adversarial_loss: 0.0802 - val_loss: 0.1132 - val_sparse_categorical_crossentropy: 0.0467 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0664\n",
      "Epoch 828/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1204 - sparse_categorical_crossentropy: 0.0476 - sparse_categorical_accuracy: 0.9831 - scaled_adversarial_loss: 0.0728 - val_loss: 0.1093 - val_sparse_categorical_crossentropy: 0.0502 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0591\n",
      "Epoch 829/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1306 - sparse_categorical_crossentropy: 0.0478 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0828 - val_loss: 0.0964 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0592\n",
      "Epoch 830/1000\n",
      "9/9 [==============================] - 3s 359ms/step - loss: 0.1254 - sparse_categorical_crossentropy: 0.0435 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0819 - val_loss: 0.0987 - val_sparse_categorical_crossentropy: 0.0463 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0524\n",
      "Epoch 831/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1112 - sparse_categorical_crossentropy: 0.0296 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0816 - val_loss: 0.0892 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0485\n",
      "Epoch 832/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0255 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0798 - val_loss: 0.1102 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0587\n",
      "Epoch 833/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1184 - sparse_categorical_crossentropy: 0.0439 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0745 - val_loss: 0.1036 - val_sparse_categorical_crossentropy: 0.0451 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0585\n",
      "Epoch 834/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1219 - sparse_categorical_crossentropy: 0.0416 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0803 - val_loss: 0.1098 - val_sparse_categorical_crossentropy: 0.0485 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 835/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1132 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0777 - val_loss: 0.1031 - val_sparse_categorical_crossentropy: 0.0497 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0534\n",
      "Epoch 836/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1146 - sparse_categorical_crossentropy: 0.0387 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0760 - val_loss: 0.1070 - val_sparse_categorical_crossentropy: 0.0387 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 837/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1148 - sparse_categorical_crossentropy: 0.0409 - sparse_categorical_accuracy: 0.9855 - scaled_adversarial_loss: 0.0739 - val_loss: 0.1235 - val_sparse_categorical_crossentropy: 0.0585 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0650\n",
      "Epoch 838/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1135 - sparse_categorical_crossentropy: 0.0334 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0801 - val_loss: 0.1084 - val_sparse_categorical_crossentropy: 0.0439 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0645\n",
      "Epoch 839/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1114 - sparse_categorical_crossentropy: 0.0301 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0812 - val_loss: 0.1087 - val_sparse_categorical_crossentropy: 0.0494 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0593\n",
      "Epoch 840/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1101 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0768 - val_loss: 0.1148 - val_sparse_categorical_crossentropy: 0.0530 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0618\n",
      "Epoch 841/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1128 - sparse_categorical_crossentropy: 0.0368 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0759 - val_loss: 0.1042 - val_sparse_categorical_crossentropy: 0.0441 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 842/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1202 - sparse_categorical_crossentropy: 0.0427 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0775 - val_loss: 0.1075 - val_sparse_categorical_crossentropy: 0.0464 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0611\n",
      "Epoch 843/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1073 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0748 - val_loss: 0.0950 - val_sparse_categorical_crossentropy: 0.0411 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0539\n",
      "Epoch 844/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1117 - sparse_categorical_crossentropy: 0.0311 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0805 - val_loss: 0.1066 - val_sparse_categorical_crossentropy: 0.0536 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0529\n",
      "Epoch 845/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.1050 - sparse_categorical_crossentropy: 0.0280 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0770 - val_loss: 0.1075 - val_sparse_categorical_crossentropy: 0.0463 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 846/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1008 - sparse_categorical_crossentropy: 0.0257 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0752 - val_loss: 0.1193 - val_sparse_categorical_crossentropy: 0.0500 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0693\n",
      "Epoch 847/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1058 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0949 - val_sparse_categorical_crossentropy: 0.0454 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0495\n",
      "Epoch 848/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1123 - sparse_categorical_crossentropy: 0.0416 - sparse_categorical_accuracy: 0.9875 - scaled_adversarial_loss: 0.0707 - val_loss: 0.1221 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0705\n",
      "Epoch 849/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1242 - sparse_categorical_crossentropy: 0.0417 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0824 - val_loss: 0.1197 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0726\n",
      "Epoch 850/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1168 - sparse_categorical_crossentropy: 0.0359 - sparse_categorical_accuracy: 0.9843 - scaled_adversarial_loss: 0.0809 - val_loss: 0.1092 - val_sparse_categorical_crossentropy: 0.0597 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0494\n",
      "Epoch 851/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1082 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0750 - val_loss: 0.1049 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0599\n",
      "Epoch 852/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.1187 - sparse_categorical_crossentropy: 0.0428 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0758 - val_loss: 0.1156 - val_sparse_categorical_crossentropy: 0.0637 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0519\n",
      "Epoch 853/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1172 - sparse_categorical_crossentropy: 0.0392 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1203 - val_sparse_categorical_crossentropy: 0.0464 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0739\n",
      "Epoch 854/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1132 - sparse_categorical_crossentropy: 0.0366 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1384 - val_sparse_categorical_crossentropy: 0.0669 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0715\n",
      "Epoch 855/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0337 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0716 - val_loss: 0.1112 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 856/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1098 - sparse_categorical_crossentropy: 0.0356 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0742 - val_loss: 0.1357 - val_sparse_categorical_crossentropy: 0.0541 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0816\n",
      "Epoch 857/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1058 - sparse_categorical_crossentropy: 0.0332 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0726 - val_loss: 0.1145 - val_sparse_categorical_crossentropy: 0.0433 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0711\n",
      "Epoch 858/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.1076 - sparse_categorical_crossentropy: 0.0321 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0755 - val_loss: 0.1080 - val_sparse_categorical_crossentropy: 0.0536 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0544\n",
      "Epoch 859/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1078 - sparse_categorical_crossentropy: 0.0309 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0769 - val_loss: 0.1324 - val_sparse_categorical_crossentropy: 0.0663 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0661\n",
      "Epoch 860/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1051 - sparse_categorical_crossentropy: 0.0291 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0759 - val_loss: 0.1191 - val_sparse_categorical_crossentropy: 0.0469 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0723\n",
      "Epoch 861/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1044 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0713 - val_loss: 0.1124 - val_sparse_categorical_crossentropy: 0.0512 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0612\n",
      "Epoch 862/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1097 - sparse_categorical_crossentropy: 0.0331 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1005 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0607\n",
      "Epoch 863/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.1043 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0767 - val_loss: 0.1141 - val_sparse_categorical_crossentropy: 0.0544 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0597\n",
      "Epoch 864/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.1015 - sparse_categorical_crossentropy: 0.0255 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0759 - val_loss: 0.1124 - val_sparse_categorical_crossentropy: 0.0504 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 865/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.0927 - sparse_categorical_crossentropy: 0.0216 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0711 - val_loss: 0.1008 - val_sparse_categorical_crossentropy: 0.0450 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0558\n",
      "Epoch 866/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.0926 - sparse_categorical_crossentropy: 0.0210 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0716 - val_loss: 0.1061 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0614\n",
      "Epoch 867/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1105 - sparse_categorical_crossentropy: 0.0339 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1083 - val_sparse_categorical_crossentropy: 0.0423 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0661\n",
      "Epoch 868/1000\n",
      "9/9 [==============================] - 3s 319ms/step - loss: 0.1036 - sparse_categorical_crossentropy: 0.0297 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0739 - val_loss: 0.1151 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0742\n",
      "Epoch 869/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1108 - sparse_categorical_crossentropy: 0.0358 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0750 - val_loss: 0.1217 - val_sparse_categorical_crossentropy: 0.0517 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0700\n",
      "Epoch 870/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.0973 - sparse_categorical_crossentropy: 0.0294 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0679 - val_loss: 0.1454 - val_sparse_categorical_crossentropy: 0.0673 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0780\n",
      "Epoch 871/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1063 - sparse_categorical_crossentropy: 0.0329 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0734 - val_loss: 0.1170 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0685\n",
      "Epoch 872/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1060 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0783 - val_loss: 0.1122 - val_sparse_categorical_crossentropy: 0.0558 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0564\n",
      "Epoch 873/1000\n",
      "9/9 [==============================] - 3s 358ms/step - loss: 0.1147 - sparse_categorical_crossentropy: 0.0388 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0760 - val_loss: 0.1079 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 874/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1015 - sparse_categorical_crossentropy: 0.0333 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0681 - val_loss: 0.1261 - val_sparse_categorical_crossentropy: 0.0448 - val_sparse_categorical_accuracy: 0.9807 - val_scaled_adversarial_loss: 0.0813\n",
      "Epoch 875/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1150 - sparse_categorical_crossentropy: 0.0370 - sparse_categorical_accuracy: 0.9867 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1306 - val_sparse_categorical_crossentropy: 0.0584 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0722\n",
      "Epoch 876/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1011 - sparse_categorical_crossentropy: 0.0292 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0718 - val_loss: 0.1220 - val_sparse_categorical_crossentropy: 0.0436 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0784\n",
      "Epoch 877/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1040 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0764 - val_loss: 0.1128 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0683\n",
      "Epoch 878/1000\n",
      "9/9 [==============================] - 3s 326ms/step - loss: 0.0943 - sparse_categorical_crossentropy: 0.0251 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0691 - val_loss: 0.1162 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0671\n",
      "Epoch 879/1000\n",
      "9/9 [==============================] - 3s 368ms/step - loss: 0.0944 - sparse_categorical_crossentropy: 0.0248 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0696 - val_loss: 0.1058 - val_sparse_categorical_crossentropy: 0.0404 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0654\n",
      "Epoch 880/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.0992 - sparse_categorical_crossentropy: 0.0256 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0737 - val_loss: 0.1117 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0643\n",
      "Epoch 881/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.0978 - sparse_categorical_crossentropy: 0.0270 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0708 - val_loss: 0.0946 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0521\n",
      "Epoch 882/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1032 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0751 - val_loss: 0.1063 - val_sparse_categorical_crossentropy: 0.0396 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0667\n",
      "Epoch 883/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.0978 - sparse_categorical_crossentropy: 0.0282 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0696 - val_loss: 0.1070 - val_sparse_categorical_crossentropy: 0.0492 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0578\n",
      "Epoch 884/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.0969 - sparse_categorical_crossentropy: 0.0246 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0724 - val_loss: 0.1121 - val_sparse_categorical_crossentropy: 0.0375 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0746\n",
      "Epoch 885/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.0990 - sparse_categorical_crossentropy: 0.0256 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0734 - val_loss: 0.1095 - val_sparse_categorical_crossentropy: 0.0459 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0636\n",
      "Epoch 886/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.0962 - sparse_categorical_crossentropy: 0.0266 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0696 - val_loss: 0.1076 - val_sparse_categorical_crossentropy: 0.0486 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0590\n",
      "Epoch 887/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.1002 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0699 - val_loss: 0.1471 - val_sparse_categorical_crossentropy: 0.0602 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0868\n",
      "Epoch 888/1000\n",
      "9/9 [==============================] - 3s 325ms/step - loss: 0.1134 - sparse_categorical_crossentropy: 0.0373 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0762 - val_loss: 0.0993 - val_sparse_categorical_crossentropy: 0.0493 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0500\n",
      "Epoch 889/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1139 - sparse_categorical_crossentropy: 0.0310 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0829 - val_loss: 0.1106 - val_sparse_categorical_crossentropy: 0.0459 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0647\n",
      "Epoch 890/1000\n",
      "9/9 [==============================] - 3s 350ms/step - loss: 0.1114 - sparse_categorical_crossentropy: 0.0358 - sparse_categorical_accuracy: 0.9899 - scaled_adversarial_loss: 0.0757 - val_loss: 0.1223 - val_sparse_categorical_crossentropy: 0.0573 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0650\n",
      "Epoch 891/1000\n",
      "9/9 [==============================] - 3s 338ms/step - loss: 0.0954 - sparse_categorical_crossentropy: 0.0254 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0977 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0505\n",
      "Epoch 892/1000\n",
      "9/9 [==============================] - 3s 375ms/step - loss: 0.1008 - sparse_categorical_crossentropy: 0.0298 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0710 - val_loss: 0.1195 - val_sparse_categorical_crossentropy: 0.0640 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 893/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1010 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0706 - val_loss: 0.0943 - val_sparse_categorical_crossentropy: 0.0415 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0528\n",
      "Epoch 894/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.0909 - sparse_categorical_crossentropy: 0.0230 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0679 - val_loss: 0.0954 - val_sparse_categorical_crossentropy: 0.0414 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0541\n",
      "Epoch 895/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.0991 - sparse_categorical_crossentropy: 0.0283 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0709 - val_loss: 0.1014 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0594\n",
      "Epoch 896/1000\n",
      "9/9 [==============================] - 4s 415ms/step - loss: 0.1100 - sparse_categorical_crossentropy: 0.0341 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0759 - val_loss: 0.1068 - val_sparse_categorical_crossentropy: 0.0445 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0623\n",
      "Epoch 897/1000\n",
      "9/9 [==============================] - 3s 348ms/step - loss: 0.1020 - sparse_categorical_crossentropy: 0.0273 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0747 - val_loss: 0.1059 - val_sparse_categorical_crossentropy: 0.0425 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0633\n",
      "Epoch 898/1000\n",
      "9/9 [==============================] - 3s 356ms/step - loss: 0.1095 - sparse_categorical_crossentropy: 0.0276 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0819 - val_loss: 0.0969 - val_sparse_categorical_crossentropy: 0.0382 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0587\n",
      "Epoch 899/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0266 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0811 - val_loss: 0.1116 - val_sparse_categorical_crossentropy: 0.0365 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0751\n",
      "Epoch 900/1000\n",
      "9/9 [==============================] - 3s 371ms/step - loss: 0.0989 - sparse_categorical_crossentropy: 0.0242 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0747 - val_loss: 0.0881 - val_sparse_categorical_crossentropy: 0.0373 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0507\n",
      "Epoch 901/1000\n",
      "9/9 [==============================] - 4s 404ms/step - loss: 0.1023 - sparse_categorical_crossentropy: 0.0318 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0705 - val_loss: 0.1042 - val_sparse_categorical_crossentropy: 0.0510 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0532\n",
      "Epoch 902/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.0989 - sparse_categorical_crossentropy: 0.0224 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0766 - val_loss: 0.0913 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0515\n",
      "Epoch 903/1000\n",
      "9/9 [==============================] - 3s 372ms/step - loss: 0.0960 - sparse_categorical_crossentropy: 0.0234 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0726 - val_loss: 0.1056 - val_sparse_categorical_crossentropy: 0.0580 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0476\n",
      "Epoch 904/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.0942 - sparse_categorical_crossentropy: 0.0221 - sparse_categorical_accuracy: 0.9928 - scaled_adversarial_loss: 0.0721 - val_loss: 0.0959 - val_sparse_categorical_crossentropy: 0.0436 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0523\n",
      "Epoch 905/1000\n",
      "9/9 [==============================] - 3s 338ms/step - loss: 0.0919 - sparse_categorical_crossentropy: 0.0198 - sparse_categorical_accuracy: 0.9937 - scaled_adversarial_loss: 0.0720 - val_loss: 0.1025 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0591\n",
      "Epoch 906/1000\n",
      "9/9 [==============================] - 3s 336ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0269 - sparse_categorical_accuracy: 0.9935 - scaled_adversarial_loss: 0.0780 - val_loss: 0.0936 - val_sparse_categorical_crossentropy: 0.0432 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0504\n",
      "Epoch 907/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.0962 - sparse_categorical_crossentropy: 0.0223 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0739 - val_loss: 0.1026 - val_sparse_categorical_crossentropy: 0.0504 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 908/1000\n",
      "9/9 [==============================] - 3s 334ms/step - loss: 0.1023 - sparse_categorical_crossentropy: 0.0238 - sparse_categorical_accuracy: 0.9928 - scaled_adversarial_loss: 0.0784 - val_loss: 0.0872 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0438\n",
      "Epoch 909/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.0956 - sparse_categorical_crossentropy: 0.0242 - sparse_categorical_accuracy: 0.9942 - scaled_adversarial_loss: 0.0714 - val_loss: 0.1164 - val_sparse_categorical_crossentropy: 0.0528 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0637\n",
      "Epoch 910/1000\n",
      "9/9 [==============================] - 3s 333ms/step - loss: 0.0978 - sparse_categorical_crossentropy: 0.0236 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0743 - val_loss: 0.1046 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0626\n",
      "Epoch 911/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.0963 - sparse_categorical_crossentropy: 0.0228 - sparse_categorical_accuracy: 0.9935 - scaled_adversarial_loss: 0.0735 - val_loss: 0.1035 - val_sparse_categorical_crossentropy: 0.0435 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0600\n",
      "Epoch 912/1000\n",
      "9/9 [==============================] - 3s 353ms/step - loss: 0.0925 - sparse_categorical_crossentropy: 0.0207 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0881 - val_sparse_categorical_crossentropy: 0.0362 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0518\n",
      "Epoch 913/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.0908 - sparse_categorical_crossentropy: 0.0202 - sparse_categorical_accuracy: 0.9940 - scaled_adversarial_loss: 0.0705 - val_loss: 0.1016 - val_sparse_categorical_crossentropy: 0.0420 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0596\n",
      "Epoch 914/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1044 - sparse_categorical_crossentropy: 0.0264 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1056 - val_sparse_categorical_crossentropy: 0.0418 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0638\n",
      "Epoch 915/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.0997 - sparse_categorical_crossentropy: 0.0284 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0713 - val_loss: 0.0885 - val_sparse_categorical_crossentropy: 0.0427 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0457\n",
      "Epoch 916/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.0914 - sparse_categorical_crossentropy: 0.0224 - sparse_categorical_accuracy: 0.9930 - scaled_adversarial_loss: 0.0690 - val_loss: 0.0923 - val_sparse_categorical_crossentropy: 0.0430 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0493\n",
      "Epoch 917/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1055 - sparse_categorical_crossentropy: 0.0302 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0753 - val_loss: 0.1218 - val_sparse_categorical_crossentropy: 0.0472 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0746\n",
      "Epoch 918/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1041 - sparse_categorical_crossentropy: 0.0284 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0757 - val_loss: 0.0940 - val_sparse_categorical_crossentropy: 0.0488 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0452\n",
      "Epoch 919/1000\n",
      "9/9 [==============================] - 3s 370ms/step - loss: 0.1088 - sparse_categorical_crossentropy: 0.0390 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0698 - val_loss: 0.0912 - val_sparse_categorical_crossentropy: 0.0363 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0549\n",
      "Epoch 920/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0534 - sparse_categorical_accuracy: 0.9812 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0990 - val_sparse_categorical_crossentropy: 0.0414 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0576\n",
      "Epoch 921/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1627 - sparse_categorical_crossentropy: 0.0907 - sparse_categorical_accuracy: 0.9672 - scaled_adversarial_loss: 0.0720 - val_loss: 0.1680 - val_sparse_categorical_crossentropy: 0.0830 - val_sparse_categorical_accuracy: 0.9759 - val_scaled_adversarial_loss: 0.0850\n",
      "Epoch 922/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1522 - sparse_categorical_crossentropy: 0.0656 - sparse_categorical_accuracy: 0.9766 - scaled_adversarial_loss: 0.0865 - val_loss: 0.1201 - val_sparse_categorical_crossentropy: 0.0505 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0696\n",
      "Epoch 923/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0451 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0755 - val_loss: 0.1239 - val_sparse_categorical_crossentropy: 0.0491 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0747\n",
      "Epoch 924/1000\n",
      "9/9 [==============================] - 3s 342ms/step - loss: 0.1046 - sparse_categorical_crossentropy: 0.0325 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0721 - val_loss: 0.1174 - val_sparse_categorical_crossentropy: 0.0532 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0641\n",
      "Epoch 925/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1108 - sparse_categorical_crossentropy: 0.0338 - sparse_categorical_accuracy: 0.9928 - scaled_adversarial_loss: 0.0770 - val_loss: 0.1069 - val_sparse_categorical_crossentropy: 0.0473 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0596\n",
      "Epoch 926/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.1023 - sparse_categorical_crossentropy: 0.0309 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0714 - val_loss: 0.0994 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0478\n",
      "Epoch 927/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.0991 - sparse_categorical_crossentropy: 0.0240 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0750 - val_loss: 0.0963 - val_sparse_categorical_crossentropy: 0.0426 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0536\n",
      "Epoch 928/1000\n",
      "9/9 [==============================] - 3s 340ms/step - loss: 0.1033 - sparse_categorical_crossentropy: 0.0320 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0713 - val_loss: 0.1038 - val_sparse_categorical_crossentropy: 0.0525 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0513\n",
      "Epoch 929/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.0954 - sparse_categorical_crossentropy: 0.0266 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0687 - val_loss: 0.1275 - val_sparse_categorical_crossentropy: 0.0710 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 930/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1036 - sparse_categorical_crossentropy: 0.0295 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0740 - val_loss: 0.0910 - val_sparse_categorical_crossentropy: 0.0409 - val_sparse_categorical_accuracy: 0.9884 - val_scaled_adversarial_loss: 0.0501\n",
      "Epoch 931/1000\n",
      "9/9 [==============================] - 3s 352ms/step - loss: 0.1055 - sparse_categorical_crossentropy: 0.0305 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0750 - val_loss: 0.1064 - val_sparse_categorical_crossentropy: 0.0561 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0503\n",
      "Epoch 932/1000\n",
      "9/9 [==============================] - 3s 380ms/step - loss: 0.1206 - sparse_categorical_crossentropy: 0.0426 - sparse_categorical_accuracy: 0.9879 - scaled_adversarial_loss: 0.0780 - val_loss: 0.1120 - val_sparse_categorical_crossentropy: 0.0433 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0687\n",
      "Epoch 933/1000\n",
      "9/9 [==============================] - 4s 406ms/step - loss: 0.1151 - sparse_categorical_crossentropy: 0.0361 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0791 - val_loss: 0.1132 - val_sparse_categorical_crossentropy: 0.0483 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0649\n",
      "Epoch 934/1000\n",
      "9/9 [==============================] - 4s 402ms/step - loss: 0.1236 - sparse_categorical_crossentropy: 0.0505 - sparse_categorical_accuracy: 0.9892 - scaled_adversarial_loss: 0.0731 - val_loss: 0.1182 - val_sparse_categorical_crossentropy: 0.0549 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0633\n",
      "Epoch 935/1000\n",
      "9/9 [==============================] - 4s 402ms/step - loss: 0.1212 - sparse_categorical_crossentropy: 0.0485 - sparse_categorical_accuracy: 0.9872 - scaled_adversarial_loss: 0.0727 - val_loss: 0.1366 - val_sparse_categorical_crossentropy: 0.0572 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0793\n",
      "Epoch 936/1000\n",
      "9/9 [==============================] - 4s 406ms/step - loss: 0.1286 - sparse_categorical_crossentropy: 0.0434 - sparse_categorical_accuracy: 0.9838 - scaled_adversarial_loss: 0.0853 - val_loss: 0.1210 - val_sparse_categorical_crossentropy: 0.0484 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0726\n",
      "Epoch 937/1000\n",
      "9/9 [==============================] - 4s 390ms/step - loss: 0.1012 - sparse_categorical_crossentropy: 0.0294 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0718 - val_loss: 0.0980 - val_sparse_categorical_crossentropy: 0.0380 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0601\n",
      "Epoch 938/1000\n",
      "9/9 [==============================] - 3s 377ms/step - loss: 0.1165 - sparse_categorical_crossentropy: 0.0398 - sparse_categorical_accuracy: 0.9858 - scaled_adversarial_loss: 0.0767 - val_loss: 0.1044 - val_sparse_categorical_crossentropy: 0.0402 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0642\n",
      "Epoch 939/1000\n",
      "9/9 [==============================] - 3s 373ms/step - loss: 0.1046 - sparse_categorical_crossentropy: 0.0306 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0740 - val_loss: 0.1099 - val_sparse_categorical_crossentropy: 0.0490 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0608\n",
      "Epoch 940/1000\n",
      "9/9 [==============================] - 3s 354ms/step - loss: 0.1077 - sparse_categorical_crossentropy: 0.0247 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0830 - val_loss: 0.0980 - val_sparse_categorical_crossentropy: 0.0423 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0557\n",
      "Epoch 941/1000\n",
      "9/9 [==============================] - 3s 369ms/step - loss: 0.1034 - sparse_categorical_crossentropy: 0.0281 - sparse_categorical_accuracy: 0.9949 - scaled_adversarial_loss: 0.0753 - val_loss: 0.0931 - val_sparse_categorical_crossentropy: 0.0367 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0564\n",
      "Epoch 942/1000\n",
      "9/9 [==============================] - 4s 388ms/step - loss: 0.0987 - sparse_categorical_crossentropy: 0.0288 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0699 - val_loss: 0.1063 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0556\n",
      "Epoch 943/1000\n",
      "9/9 [==============================] - 3s 365ms/step - loss: 0.1015 - sparse_categorical_crossentropy: 0.0242 - sparse_categorical_accuracy: 0.9928 - scaled_adversarial_loss: 0.0773 - val_loss: 0.0984 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0618\n",
      "Epoch 944/1000\n",
      "9/9 [==============================] - 3s 390ms/step - loss: 0.1041 - sparse_categorical_crossentropy: 0.0252 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0789 - val_loss: 0.1123 - val_sparse_categorical_crossentropy: 0.0520 - val_sparse_categorical_accuracy: 0.9798 - val_scaled_adversarial_loss: 0.0603\n",
      "Epoch 945/1000\n",
      "9/9 [==============================] - 4s 409ms/step - loss: 0.0975 - sparse_categorical_crossentropy: 0.0249 - sparse_categorical_accuracy: 0.9935 - scaled_adversarial_loss: 0.0726 - val_loss: 0.0945 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0511\n",
      "Epoch 946/1000\n",
      "9/9 [==============================] - 4s 402ms/step - loss: 0.0978 - sparse_categorical_crossentropy: 0.0244 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0734 - val_loss: 0.0875 - val_sparse_categorical_crossentropy: 0.0364 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0512\n",
      "Epoch 947/1000\n",
      "9/9 [==============================] - 4s 396ms/step - loss: 0.1009 - sparse_categorical_crossentropy: 0.0269 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0740 - val_loss: 0.1040 - val_sparse_categorical_crossentropy: 0.0426 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0613\n",
      "Epoch 948/1000\n",
      "9/9 [==============================] - 3s 392ms/step - loss: 0.1168 - sparse_categorical_crossentropy: 0.0335 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0833 - val_loss: 0.0990 - val_sparse_categorical_crossentropy: 0.0383 - val_sparse_categorical_accuracy: 0.9884 - val_scaled_adversarial_loss: 0.0607\n",
      "Epoch 949/1000\n",
      "9/9 [==============================] - 4s 441ms/step - loss: 0.1141 - sparse_categorical_crossentropy: 0.0438 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0703 - val_loss: 0.1180 - val_sparse_categorical_crossentropy: 0.0432 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0748\n",
      "Epoch 950/1000\n",
      "9/9 [==============================] - 3s 362ms/step - loss: 0.1343 - sparse_categorical_crossentropy: 0.0514 - sparse_categorical_accuracy: 0.9831 - scaled_adversarial_loss: 0.0828 - val_loss: 0.1124 - val_sparse_categorical_crossentropy: 0.0428 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0697\n",
      "Epoch 951/1000\n",
      "9/9 [==============================] - 3s 345ms/step - loss: 0.1133 - sparse_categorical_crossentropy: 0.0330 - sparse_categorical_accuracy: 0.9877 - scaled_adversarial_loss: 0.0803 - val_loss: 0.1187 - val_sparse_categorical_crossentropy: 0.0536 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0651\n",
      "Epoch 952/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1026 - sparse_categorical_crossentropy: 0.0263 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0763 - val_loss: 0.1519 - val_sparse_categorical_crossentropy: 0.0568 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0950\n",
      "Epoch 953/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1054 - sparse_categorical_crossentropy: 0.0287 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0920 - val_sparse_categorical_crossentropy: 0.0406 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 954/1000\n",
      "9/9 [==============================] - 3s 363ms/step - loss: 0.1024 - sparse_categorical_crossentropy: 0.0261 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0763 - val_loss: 0.1067 - val_sparse_categorical_crossentropy: 0.0416 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0650\n",
      "Epoch 955/1000\n",
      "9/9 [==============================] - 4s 406ms/step - loss: 0.1010 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0744 - val_loss: 0.1136 - val_sparse_categorical_crossentropy: 0.0515 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0620\n",
      "Epoch 956/1000\n",
      "9/9 [==============================] - 3s 384ms/step - loss: 0.1057 - sparse_categorical_crossentropy: 0.0326 - sparse_categorical_accuracy: 0.9882 - scaled_adversarial_loss: 0.0731 - val_loss: 0.0975 - val_sparse_categorical_crossentropy: 0.0366 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0609\n",
      "Epoch 957/1000\n",
      "9/9 [==============================] - 3s 389ms/step - loss: 0.1064 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0799 - val_loss: 0.0991 - val_sparse_categorical_crossentropy: 0.0355 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0636\n",
      "Epoch 958/1000\n",
      "9/9 [==============================] - 4s 395ms/step - loss: 0.1124 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0773 - val_loss: 0.1173 - val_sparse_categorical_crossentropy: 0.0443 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0730\n",
      "Epoch 959/1000\n",
      "9/9 [==============================] - 3s 388ms/step - loss: 0.1125 - sparse_categorical_crossentropy: 0.0379 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0746 - val_loss: 0.1012 - val_sparse_categorical_crossentropy: 0.0419 - val_sparse_categorical_accuracy: 0.9884 - val_scaled_adversarial_loss: 0.0593\n",
      "Epoch 960/1000\n",
      "9/9 [==============================] - 3s 357ms/step - loss: 0.1027 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0752 - val_loss: 0.0946 - val_sparse_categorical_crossentropy: 0.0379 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0567\n",
      "Epoch 961/1000\n",
      "9/9 [==============================] - 3s 341ms/step - loss: 0.0868 - sparse_categorical_crossentropy: 0.0215 - sparse_categorical_accuracy: 0.9928 - scaled_adversarial_loss: 0.0654 - val_loss: 0.1045 - val_sparse_categorical_crossentropy: 0.0389 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0657\n",
      "Epoch 962/1000\n",
      "9/9 [==============================] - 3s 344ms/step - loss: 0.0955 - sparse_categorical_crossentropy: 0.0245 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0710 - val_loss: 0.0974 - val_sparse_categorical_crossentropy: 0.0421 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0552\n",
      "Epoch 963/1000\n",
      "9/9 [==============================] - 3s 360ms/step - loss: 0.1002 - sparse_categorical_crossentropy: 0.0260 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0742 - val_loss: 0.1116 - val_sparse_categorical_crossentropy: 0.0507 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0609\n",
      "Epoch 964/1000\n",
      "9/9 [==============================] - 3s 343ms/step - loss: 0.1018 - sparse_categorical_crossentropy: 0.0289 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0729 - val_loss: 0.1019 - val_sparse_categorical_crossentropy: 0.0438 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0580\n",
      "Epoch 965/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1049 - sparse_categorical_crossentropy: 0.0309 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0739 - val_loss: 0.1141 - val_sparse_categorical_crossentropy: 0.0584 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0557\n",
      "Epoch 966/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.0970 - sparse_categorical_crossentropy: 0.0230 - sparse_categorical_accuracy: 0.9925 - scaled_adversarial_loss: 0.0740 - val_loss: 0.1099 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0675\n",
      "Epoch 967/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1014 - sparse_categorical_crossentropy: 0.0247 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0767 - val_loss: 0.0891 - val_sparse_categorical_crossentropy: 0.0370 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0522\n",
      "Epoch 968/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.0933 - sparse_categorical_crossentropy: 0.0293 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0640 - val_loss: 0.1425 - val_sparse_categorical_crossentropy: 0.0621 - val_sparse_categorical_accuracy: 0.9827 - val_scaled_adversarial_loss: 0.0804\n",
      "Epoch 969/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.1068 - sparse_categorical_crossentropy: 0.0327 - sparse_categorical_accuracy: 0.9894 - scaled_adversarial_loss: 0.0740 - val_loss: 0.1075 - val_sparse_categorical_crossentropy: 0.0517 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0558\n",
      "Epoch 970/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1028 - sparse_categorical_crossentropy: 0.0343 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0685 - val_loss: 0.1105 - val_sparse_categorical_crossentropy: 0.0556 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0549\n",
      "Epoch 971/1000\n",
      "9/9 [==============================] - 3s 329ms/step - loss: 0.1079 - sparse_categorical_crossentropy: 0.0327 - sparse_categorical_accuracy: 0.9889 - scaled_adversarial_loss: 0.0752 - val_loss: 0.1258 - val_sparse_categorical_crossentropy: 0.0551 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0707\n",
      "Epoch 972/1000\n",
      "9/9 [==============================] - 3s 331ms/step - loss: 0.0991 - sparse_categorical_crossentropy: 0.0339 - sparse_categorical_accuracy: 0.9896 - scaled_adversarial_loss: 0.0652 - val_loss: 0.1127 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0602\n",
      "Epoch 973/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1001 - sparse_categorical_crossentropy: 0.0274 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0727 - val_loss: 0.1171 - val_sparse_categorical_crossentropy: 0.0502 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0669\n",
      "Epoch 974/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.0945 - sparse_categorical_crossentropy: 0.0216 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0729 - val_loss: 0.1223 - val_sparse_categorical_crossentropy: 0.0663 - val_sparse_categorical_accuracy: 0.9778 - val_scaled_adversarial_loss: 0.0561\n",
      "Epoch 975/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.0966 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0698 - val_loss: 0.1096 - val_sparse_categorical_crossentropy: 0.0499 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0597\n",
      "Epoch 976/1000\n",
      "9/9 [==============================] - 3s 332ms/step - loss: 0.0964 - sparse_categorical_crossentropy: 0.0265 - sparse_categorical_accuracy: 0.9904 - scaled_adversarial_loss: 0.0699 - val_loss: 0.0898 - val_sparse_categorical_crossentropy: 0.0412 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0486\n",
      "Epoch 977/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.0997 - sparse_categorical_crossentropy: 0.0268 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0729 - val_loss: 0.1098 - val_sparse_categorical_crossentropy: 0.0521 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0577\n",
      "Epoch 978/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1161 - sparse_categorical_crossentropy: 0.0415 - sparse_categorical_accuracy: 0.9851 - scaled_adversarial_loss: 0.0746 - val_loss: 0.1336 - val_sparse_categorical_crossentropy: 0.0668 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0668\n",
      "Epoch 979/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.1296 - sparse_categorical_crossentropy: 0.0484 - sparse_categorical_accuracy: 0.9841 - scaled_adversarial_loss: 0.0812 - val_loss: 0.0959 - val_sparse_categorical_crossentropy: 0.0398 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0560\n",
      "Epoch 980/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1080 - sparse_categorical_crossentropy: 0.0351 - sparse_categorical_accuracy: 0.9860 - scaled_adversarial_loss: 0.0729 - val_loss: 0.1092 - val_sparse_categorical_crossentropy: 0.0466 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0625\n",
      "Epoch 981/1000\n",
      "9/9 [==============================] - 3s 327ms/step - loss: 0.1082 - sparse_categorical_crossentropy: 0.0355 - sparse_categorical_accuracy: 0.9863 - scaled_adversarial_loss: 0.0727 - val_loss: 0.1258 - val_sparse_categorical_crossentropy: 0.0638 - val_sparse_categorical_accuracy: 0.9788 - val_scaled_adversarial_loss: 0.0621\n",
      "Epoch 982/1000\n",
      "9/9 [==============================] - 3s 335ms/step - loss: 0.0989 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0722 - val_loss: 0.1002 - val_sparse_categorical_crossentropy: 0.0436 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0565\n",
      "Epoch 983/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.0945 - sparse_categorical_crossentropy: 0.0266 - sparse_categorical_accuracy: 0.9901 - scaled_adversarial_loss: 0.0678 - val_loss: 0.1169 - val_sparse_categorical_crossentropy: 0.0554 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0614\n",
      "Epoch 984/1000\n",
      "9/9 [==============================] - 3s 328ms/step - loss: 0.0892 - sparse_categorical_crossentropy: 0.0206 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0686 - val_loss: 0.0816 - val_sparse_categorical_crossentropy: 0.0368 - val_sparse_categorical_accuracy: 0.9884 - val_scaled_adversarial_loss: 0.0449\n",
      "Epoch 985/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1057 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9906 - scaled_adversarial_loss: 0.0752 - val_loss: 0.1040 - val_sparse_categorical_crossentropy: 0.0526 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0514\n",
      "Epoch 986/1000\n",
      "9/9 [==============================] - 3s 347ms/step - loss: 0.0934 - sparse_categorical_crossentropy: 0.0231 - sparse_categorical_accuracy: 0.9918 - scaled_adversarial_loss: 0.0703 - val_loss: 0.1108 - val_sparse_categorical_crossentropy: 0.0447 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0661\n",
      "Epoch 987/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.0937 - sparse_categorical_crossentropy: 0.0231 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0706 - val_loss: 0.1074 - val_sparse_categorical_crossentropy: 0.0496 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0579\n",
      "Epoch 988/1000\n",
      "9/9 [==============================] - 3s 361ms/step - loss: 0.0846 - sparse_categorical_crossentropy: 0.0159 - sparse_categorical_accuracy: 0.9937 - scaled_adversarial_loss: 0.0687 - val_loss: 0.1175 - val_sparse_categorical_crossentropy: 0.0542 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0633\n",
      "Epoch 989/1000\n",
      "9/9 [==============================] - 3s 364ms/step - loss: 0.0951 - sparse_categorical_crossentropy: 0.0250 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0701 - val_loss: 0.1046 - val_sparse_categorical_crossentropy: 0.0503 - val_sparse_categorical_accuracy: 0.9865 - val_scaled_adversarial_loss: 0.0543\n",
      "Epoch 990/1000\n",
      "9/9 [==============================] - 3s 346ms/step - loss: 0.1048 - sparse_categorical_crossentropy: 0.0283 - sparse_categorical_accuracy: 0.9935 - scaled_adversarial_loss: 0.0765 - val_loss: 0.0926 - val_sparse_categorical_crossentropy: 0.0376 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0551\n",
      "Epoch 991/1000\n",
      "9/9 [==============================] - 3s 349ms/step - loss: 0.1058 - sparse_categorical_crossentropy: 0.0253 - sparse_categorical_accuracy: 0.9916 - scaled_adversarial_loss: 0.0805 - val_loss: 0.0897 - val_sparse_categorical_crossentropy: 0.0434 - val_sparse_categorical_accuracy: 0.9836 - val_scaled_adversarial_loss: 0.0462\n",
      "Epoch 992/1000\n",
      "9/9 [==============================] - 3s 337ms/step - loss: 0.1103 - sparse_categorical_crossentropy: 0.0337 - sparse_categorical_accuracy: 0.9913 - scaled_adversarial_loss: 0.0766 - val_loss: 0.1073 - val_sparse_categorical_crossentropy: 0.0454 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0619\n",
      "Epoch 993/1000\n",
      "9/9 [==============================] - 3s 351ms/step - loss: 0.1160 - sparse_categorical_crossentropy: 0.0395 - sparse_categorical_accuracy: 0.9865 - scaled_adversarial_loss: 0.0765 - val_loss: 0.1050 - val_sparse_categorical_crossentropy: 0.0424 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0626\n",
      "Epoch 994/1000\n",
      "9/9 [==============================] - 3s 330ms/step - loss: 0.1134 - sparse_categorical_crossentropy: 0.0304 - sparse_categorical_accuracy: 0.9887 - scaled_adversarial_loss: 0.0830 - val_loss: 0.0859 - val_sparse_categorical_crossentropy: 0.0387 - val_sparse_categorical_accuracy: 0.9855 - val_scaled_adversarial_loss: 0.0472\n",
      "Epoch 995/1000\n",
      "9/9 [==============================] - 3s 339ms/step - loss: 0.1022 - sparse_categorical_crossentropy: 0.0278 - sparse_categorical_accuracy: 0.9908 - scaled_adversarial_loss: 0.0745 - val_loss: 0.0948 - val_sparse_categorical_crossentropy: 0.0471 - val_sparse_categorical_accuracy: 0.9817 - val_scaled_adversarial_loss: 0.0477\n",
      "Epoch 996/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1120 - sparse_categorical_crossentropy: 0.0294 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0826 - val_loss: 0.1090 - val_sparse_categorical_crossentropy: 0.0453 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0637\n",
      "Epoch 997/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1026 - sparse_categorical_crossentropy: 0.0273 - sparse_categorical_accuracy: 0.9923 - scaled_adversarial_loss: 0.0753 - val_loss: 0.1020 - val_sparse_categorical_crossentropy: 0.0511 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0509\n",
      "Epoch 998/1000\n",
      "9/9 [==============================] - 3s 322ms/step - loss: 0.0941 - sparse_categorical_crossentropy: 0.0231 - sparse_categorical_accuracy: 0.9932 - scaled_adversarial_loss: 0.0711 - val_loss: 0.1230 - val_sparse_categorical_crossentropy: 0.0478 - val_sparse_categorical_accuracy: 0.9875 - val_scaled_adversarial_loss: 0.0752\n",
      "Epoch 999/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.1039 - sparse_categorical_crossentropy: 0.0267 - sparse_categorical_accuracy: 0.9911 - scaled_adversarial_loss: 0.0772 - val_loss: 0.1135 - val_sparse_categorical_crossentropy: 0.0476 - val_sparse_categorical_accuracy: 0.9846 - val_scaled_adversarial_loss: 0.0659\n",
      "Epoch 1000/1000\n",
      "9/9 [==============================] - 3s 323ms/step - loss: 0.0971 - sparse_categorical_crossentropy: 0.0250 - sparse_categorical_accuracy: 0.9920 - scaled_adversarial_loss: 0.0720 - val_loss: 0.1028 - val_sparse_categorical_crossentropy: 0.0372 - val_sparse_categorical_accuracy: 0.9884 - val_scaled_adversarial_loss: 0.0656\n"
     ]
    },
    {
     "data": {
      "text/plain": "<keras.callbacks.History at 0x1e480bd6c70>"
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adv_model.fit({'feature': X_train, 'label': y_train}, epochs=1000, batch_size=512, validation_data={'feature': X_test, 'label': y_test})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "Pmt7mlJoQ-Np",
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1038/1038 [==============================] - 7s 7ms/step - loss: 0.1154 - sparse_categorical_crossentropy: 0.0536 - sparse_categorical_accuracy: 0.9884 - scaled_adversarial_loss: 0.0618\n"
     ]
    },
    {
     "data": {
      "text/plain": "[0.11543173342943192,\n 0.05363653972744942,\n 0.9884393215179443,\n 0.06179514899849892]"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adv_model.evaluate({'feature': X_test, 'label': y_test}, batch_size=1)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": [],
   "mount_file_id": "1l_2YpamsRqa2kvQbF6VcRh1L-ZVNw2LN",
   "authorship_tag": "ABX9TyOZ6tqQxYPy3g7WnP4d6Wrs"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "name": "python3"
  },
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}